This document discusses information behaviors in the U.S. intelligence community. It notes that intelligence analysts experience information overload due to the vast amounts of data they must process each day from numerous sources. This overload can compromise their efficiency and ability to identify threats in a timely manner. The document also examines issues between different levels of government in the intelligence community, such as a lack of consistent training and information sharing between federal, state, and local agencies. It proposes applying theories of information behavior from library and information science, such as minimizing effort, to help analysts better manage information overload.
The goal of this project was to determine the relationship between privacy risk and data utility when using aggregated mobile data for policy planning and crisis response. The project assessed these factors for transportation planning and pandemic control using simulated mobile call data. Experts in these domains evaluated the utility of various aggregation levels for their work. Re-identification risk was also measured for each data set. Results showed that while aggregation reduced risk, it also reduced utility, and this relationship varied by context and purpose. The project aims to help develop evidence-based standards for using mobile data proportionately based on balancing privacy risk and social benefits. Further research is needed applying this methodology to more scenarios and experts to better understand how data aggregation can enable use of mobile data for public
ANALYSIS OF TOPIC MODELING WITH UNPOOLED AND POOLED TWEETS AND EXPLORATION OF...IJCSEA Journal
In this digital era, social media is an important tool for information dissemination. Twitter is a popular social media platform. Social media analytics helps make informed decisions based on people's needs and opinions. This information, when properly perceived provides valuable insights into different domains, such as public policymaking, marketing, sales, and healthcare. Topic modeling is an unsupervised algorithm to discover a hidden pattern in text documents. In this study, we explore the Latent Dirichlet Allocation (LDA) topic model algorithm. We collected tweets with hashtags related to corona virus related discussions. This study compares regular LDA and LDA based on collapsed Gibbs sampling (LDAMallet) algorithms. The experiments use different data processing steps including trigrams, without trigrams, hashtags, and without hashtags. This study provides a comprehensive analysis of LDA for short text messages using un-pooled and pooled tweets. The results suggest that a pooling scheme using hashtags helps improve the topic inference results with a better coherence score.
TERRORIST WATCHER: AN INTERACTIVE WEBBASED VISUAL ANALYTICAL TOOL OF TERRORIS...IJDKP
Terrorism is a phenomenon that rose to its peak nowadays. Counter terrorism analysts work with a large
set of documents related to different terrorist groups and attack types to extract useful information about
these groups’ motive and tactics. It is evident that terrorism became a global threat and can exist
anywhere. In order to face this phenomenon, there is a need to understand the characteristics of the
terrorists in order to find if there are general characteristics among all of them or not. However, as the
number of the collected documents increase, deducing results and making decisions became more and
more difficult to the analysts. The use of information visualization tools can help the analysts to visualize
the terrorist characteristics. However, most of the current information visualization tools focus only on
representing and analyzing the terrorist organizations, with little emphasis on terrorist’s personal
characteristics. Therefore, the current paper presents a visualization tool that can be used to analyze the
terrorist’s personal characteristics in order to understand the production life cycle of a terrorist and how
to face it.
Computational Social Science as the Ultimate Web IntelligenceAmit Sheth
Panel at Web Intelligence, Dec 4-6, 2018, Santiago Chile
Funding Acknowledgement: Research supported in part by:
NSF Award#: CNS 1513721 TWC SBE: Medium: Context-Aware Harassment Detection on Social Media.
View represented are those of the speaker/author, and not of the sponsor.
This document discusses strategic intelligence in local law enforcement applications. It argues that while intelligence sharing has improved between federal, state, and local levels, local law enforcement needs to further develop strategic intelligence strategies. Strategic intelligence can help law enforcement identify crime trends, shape programs and policies. The document suggests that community policing models which emphasize community partnerships, organizational transformation, and problem solving can help maximize the potential for applying strategic intelligence at the local level. Implementing approaches like intelligence-led policing, CompStat, and COPPS (Community Oriented Policing and Problem Solving) may help leverage the intersection of local law enforcement and strategic intelligence.
Federal Statistical System, Transparency Camp Westbradstenger
Peter Orszag, the Director of the Office of Management and Budget, cites "evidence-based policy" to support healthcare reform. However, his evidence comes from Dartmouth University rather than the Federal Statistical System overseen by Katherine Wallman. The statistical system faces challenges in meeting transparency goals due to cultural and technical issues. While statistics are underfunded at just $10-25 per taxpayer, they provide crucial information and were important in WWII. Collaboration between journalists, programmers, statisticians, and policymakers could help improve the system.
Understanding Online Socials Harm: Examples of Harassment and RadicalizationAmit Sheth
https://dbsec2019.cse.sc.edu/Keynote.html
Abstract: As social media permeates our daily life, there has been a sharp rise in the misuse of social media affecting our society in large. Specifically, harassment and radicalization have become two major problems on social media platforms with significant implications on the well-being of individuals as well as communities. A 2017 Pew Research survey on online harassment found that 66% of adult Internet users have observed online harassment and 41% have personally experienced it. Nearly 18% of Americans have faced severe forms of harassment online such as physical threats, harassment over a sustained period, sexual harassment or stalking. Moreover, malicious organizations (e.g., terrorist groups, white nationalists not classified legally as terrorists but as a group with extreme ideology) have been using social media for sharing their propaganda and misinformation to persuade individuals and eventually recruit them to propagate their ideology. These communications related to harassment and radicalization are complex concerning their language and contextual characteristics, making recognition of such narratives challenging for researchers as well as social media companies. As most of the existing approaches fail to capture fundamental nuances in the language of these communications, two prominent challenges have emerged: ambiguity and sparsity. Sole data level bottom-up analysis has been unsuccessful in revealing the actual meaning of the content. Considering the significant sensitivity of these problems and its implications at individual and community levels, a potential solution requires reliable algorithms for modeling such communications.
Our approach to understanding communications between source and target requires deciphering the unique language, semantic and contextual characteristics, including sentiment, emotion, and intention. This context-aware and knowledge-enhanced computational approach to the analysis of these narratives breaks down this long-running and complex process into contextual building blocks that acknowledge inherent ambiguity and sparsity. Based on prior empirical and qualitative research in social sciences, particularly cognitive psychology, and political science, we model this process using a combination of contextual dimensions -- e.g., for Islamist radicalization: religion, ideology, and hate -- each elucidating a degree of radicalization and highlighting independent features to render them computationally accessible.
The document provides background on a research project investigating the data breach at the U.S. Office of Personnel Management in 2015. The project aims to interview OPM executives to understand the breach and analyze the relationship between cyber attacks and upgrades to the agency's technology. The researcher plans to enter the OPM for 3 weeks to conduct interviews and examine how often software/hardware patches are implemented each year.
The goal of this project was to determine the relationship between privacy risk and data utility when using aggregated mobile data for policy planning and crisis response. The project assessed these factors for transportation planning and pandemic control using simulated mobile call data. Experts in these domains evaluated the utility of various aggregation levels for their work. Re-identification risk was also measured for each data set. Results showed that while aggregation reduced risk, it also reduced utility, and this relationship varied by context and purpose. The project aims to help develop evidence-based standards for using mobile data proportionately based on balancing privacy risk and social benefits. Further research is needed applying this methodology to more scenarios and experts to better understand how data aggregation can enable use of mobile data for public
ANALYSIS OF TOPIC MODELING WITH UNPOOLED AND POOLED TWEETS AND EXPLORATION OF...IJCSEA Journal
In this digital era, social media is an important tool for information dissemination. Twitter is a popular social media platform. Social media analytics helps make informed decisions based on people's needs and opinions. This information, when properly perceived provides valuable insights into different domains, such as public policymaking, marketing, sales, and healthcare. Topic modeling is an unsupervised algorithm to discover a hidden pattern in text documents. In this study, we explore the Latent Dirichlet Allocation (LDA) topic model algorithm. We collected tweets with hashtags related to corona virus related discussions. This study compares regular LDA and LDA based on collapsed Gibbs sampling (LDAMallet) algorithms. The experiments use different data processing steps including trigrams, without trigrams, hashtags, and without hashtags. This study provides a comprehensive analysis of LDA for short text messages using un-pooled and pooled tweets. The results suggest that a pooling scheme using hashtags helps improve the topic inference results with a better coherence score.
TERRORIST WATCHER: AN INTERACTIVE WEBBASED VISUAL ANALYTICAL TOOL OF TERRORIS...IJDKP
Terrorism is a phenomenon that rose to its peak nowadays. Counter terrorism analysts work with a large
set of documents related to different terrorist groups and attack types to extract useful information about
these groups’ motive and tactics. It is evident that terrorism became a global threat and can exist
anywhere. In order to face this phenomenon, there is a need to understand the characteristics of the
terrorists in order to find if there are general characteristics among all of them or not. However, as the
number of the collected documents increase, deducing results and making decisions became more and
more difficult to the analysts. The use of information visualization tools can help the analysts to visualize
the terrorist characteristics. However, most of the current information visualization tools focus only on
representing and analyzing the terrorist organizations, with little emphasis on terrorist’s personal
characteristics. Therefore, the current paper presents a visualization tool that can be used to analyze the
terrorist’s personal characteristics in order to understand the production life cycle of a terrorist and how
to face it.
Computational Social Science as the Ultimate Web IntelligenceAmit Sheth
Panel at Web Intelligence, Dec 4-6, 2018, Santiago Chile
Funding Acknowledgement: Research supported in part by:
NSF Award#: CNS 1513721 TWC SBE: Medium: Context-Aware Harassment Detection on Social Media.
View represented are those of the speaker/author, and not of the sponsor.
This document discusses strategic intelligence in local law enforcement applications. It argues that while intelligence sharing has improved between federal, state, and local levels, local law enforcement needs to further develop strategic intelligence strategies. Strategic intelligence can help law enforcement identify crime trends, shape programs and policies. The document suggests that community policing models which emphasize community partnerships, organizational transformation, and problem solving can help maximize the potential for applying strategic intelligence at the local level. Implementing approaches like intelligence-led policing, CompStat, and COPPS (Community Oriented Policing and Problem Solving) may help leverage the intersection of local law enforcement and strategic intelligence.
Federal Statistical System, Transparency Camp Westbradstenger
Peter Orszag, the Director of the Office of Management and Budget, cites "evidence-based policy" to support healthcare reform. However, his evidence comes from Dartmouth University rather than the Federal Statistical System overseen by Katherine Wallman. The statistical system faces challenges in meeting transparency goals due to cultural and technical issues. While statistics are underfunded at just $10-25 per taxpayer, they provide crucial information and were important in WWII. Collaboration between journalists, programmers, statisticians, and policymakers could help improve the system.
Understanding Online Socials Harm: Examples of Harassment and RadicalizationAmit Sheth
https://dbsec2019.cse.sc.edu/Keynote.html
Abstract: As social media permeates our daily life, there has been a sharp rise in the misuse of social media affecting our society in large. Specifically, harassment and radicalization have become two major problems on social media platforms with significant implications on the well-being of individuals as well as communities. A 2017 Pew Research survey on online harassment found that 66% of adult Internet users have observed online harassment and 41% have personally experienced it. Nearly 18% of Americans have faced severe forms of harassment online such as physical threats, harassment over a sustained period, sexual harassment or stalking. Moreover, malicious organizations (e.g., terrorist groups, white nationalists not classified legally as terrorists but as a group with extreme ideology) have been using social media for sharing their propaganda and misinformation to persuade individuals and eventually recruit them to propagate their ideology. These communications related to harassment and radicalization are complex concerning their language and contextual characteristics, making recognition of such narratives challenging for researchers as well as social media companies. As most of the existing approaches fail to capture fundamental nuances in the language of these communications, two prominent challenges have emerged: ambiguity and sparsity. Sole data level bottom-up analysis has been unsuccessful in revealing the actual meaning of the content. Considering the significant sensitivity of these problems and its implications at individual and community levels, a potential solution requires reliable algorithms for modeling such communications.
Our approach to understanding communications between source and target requires deciphering the unique language, semantic and contextual characteristics, including sentiment, emotion, and intention. This context-aware and knowledge-enhanced computational approach to the analysis of these narratives breaks down this long-running and complex process into contextual building blocks that acknowledge inherent ambiguity and sparsity. Based on prior empirical and qualitative research in social sciences, particularly cognitive psychology, and political science, we model this process using a combination of contextual dimensions -- e.g., for Islamist radicalization: religion, ideology, and hate -- each elucidating a degree of radicalization and highlighting independent features to render them computationally accessible.
The document provides background on a research project investigating the data breach at the U.S. Office of Personnel Management in 2015. The project aims to interview OPM executives to understand the breach and analyze the relationship between cyber attacks and upgrades to the agency's technology. The researcher plans to enter the OPM for 3 weeks to conduct interviews and examine how often software/hardware patches are implemented each year.
disinformation risk management: leveraging cyber security best practices to s...Sara-Jayne Terp
This document discusses leveraging cybersecurity best practices to support cognitive security goals related to disinformation and misinformation. It outlines three layers of security - physical, cyber, and cognitive security. It then provides examples of cognitive security risk assessment and mapping the risk landscape. Next, it discusses working together to mitigate and respond to risks through proposed cognitive security operations centers. Finally, it provides a hypothetical example of conducting a country-level risk assessment and designing a response strategy. The document advocates adapting frameworks and standards from cybersecurity to help conceptualize and coordinate cognitive security challenges and responses.
Helping Crisis Responders Find the Informative Needle in the Tweet HaystackCOMRADES project
Leon Derczynski - University of Sheffield,
Kenny Meesters - TU Delft, Kalina Bontcheva - University of Sheffield, Diana Maynard- University of Sheffield
WiPe Paper – Social Media Studies
Proceedings of the 15th ISCRAM Conference – Rochester, NY, USA May 2018
Big data analytics: from threatening privacy to challenging democracySamos2019Summit
Big data analytics pose threats to individual and group privacy that can undermine key aspects of democracy. The use of big data for political targeting and messaging allows extensive profiling, prediction of views and behaviors, and manipulation of opinions. Over time, this can fragment political messages, obstruct open debate, and chill political expression through surveillance and the risk of being inaccurately profiled. Protecting privacy is important for maintaining fair elections and pluralism of ideas.
There are numerous ways to analyse the web information, generally web substance are housed in
large information sets and basic inquiries are utilized to parse such information sets. As the requests
expanded with time, mining web information amended to meet challenging task in a web analysis.
Machine learning methodologies are the most up to date one to go into these analysis forms. Different
approaches like decision trees, association rules, Meta heuristic and basic learning methods are embraced
for making web data appraisal and mining data from various web instances. This study will highlight these
approaches in perspective of web investigation. One of the prime goals of this exploration is to investigate
more data mining approaches alongside machine learning systems, and to express emerging collaboration
of web analytics with artificial intelligence.
Data-Mining Twitter for Political Science -Hickman, Alfredo - Honors ThesisAlfredo Hickman
This thesis examines the creation of a data mining system to extract, process, and analyze tweets from Twitter for use in political science research. The author builds an information system that collects Twitter data in real-time from a random list of 279 Members of Congress. The tweets and accompanying metadata are analyzed to provide insights into political behavior and discourse. By studying uncensored political discussions online, researchers can better understand important issues, how information spreads, and identify political networks. Analyzing social media can advance understanding of government communication and enhance research on political deliberation.
Human Trafficking-A Perspective from Computer Science and Organizational Lead...Turner Sparks
This document discusses using an interdisciplinary approach to address the issue of human trafficking. It focuses on how perspectives from computer science and organizational leadership can help law enforcement utilize surveillance and tracking software. The author conducted a literature review and found that better software for facial recognition and human tracking could be developed. However, current technology works best in controlled environments and laws need to regulate privacy issues related to increased video surveillance. Overall, the document argues that further advancing surveillance technology and providing more training to law enforcement on human trafficking should be priorities to help solve this problem.
Social Media play a critical role during crisis events, revealing a natural coordination dynamic. We propose a computational framework guided by social science principles to measure, analyze, and understand coordination among the different types of organizations and actors in crisis response. The analysis informs both the scientific account of cooperative behavior and the design of applications and protocols to support crisis management.
H. Purohit, A. Hampton, V. Shalin, A. Sheth, J. Flach. Framework to Analyze Coordination in Crisis Response. Workshop on Collaboration and Crisis Informatics, CSCW-2012.
http://knoesis.wright.edu/library/resource.php?id=1640
Clustering analysis on news from health OSINT data regarding CORONAVIRUS-COVI...ALexandruDaia1
Our primarly goal was to detect clusters via gensim libraries in news data consisting ofinformation regarding health and threats. We identified clusters for the periodscorresponding: i) Jannuary 2006 until the end of 2019, as December 2019 is considered thefirst month in which information about CORONVIRUS COVID-19 was made public; ii)between the 1st of Jannuary 2019 and 31st December 2019; and iii) between the 31st ofDecember 2019 and the 14th of April 2020. We conducted experiments using naturallanguage on open source intelligence data offered generously by brica.de, a providerspecialized in Business Risk Intelligence & Cyberthreat Awareness.
The document summarizes challenges facing the Department of Homeland Security (DHS) in acquiring and applying national intelligence. It notes that while DHS has made progress, it still struggles with issues like properly classifying critical infrastructure and prioritizing security efforts. The literature suggests DHS should adopt a risk-based approach to identify the most critical facilities and assess potential threats, rather than treating all infrastructure as equally important. This would help DHS focus its resources on the most significant security risks facing the United States.
IRJET - Political Orientation Prediction using Social Media ActivityIRJET Journal
This document discusses research into predicting the political orientation of Twitter users based on their social media activity. The researchers aim to incorporate factors like tweets, retweets, followers, followees, and network connections to better understand how political views are expressed and shaped on Twitter. Prior studies that have analyzed political bias in media outlets and the spread of information across partisan networks on social media are reviewed. The researchers describe collecting and analyzing Twitter data including tweets, retweets, mentions, followers and who a user follows to predict individual users' political leanings.
Using Financial Transaction Data To Measure Economic Resilience To Natural Di...UN Global Pulse
This project explored how financial transaction data can be analysed to better understand the economic resilience of people affected by natural disasters. The project used the Mexican state of Baja California Sur as a case study to assess the impact of Hurricane Odile on livelihoods and economic activities over a period of six months in 2014. The project measured daily Point of Sale transactions and ATM withdrawals at high geospatial resolution to gain insight into the way people prepare for and recover from disaster.
The study revealed that people spent 50% more than usual on items such as food and gasoline in preparation for the hurricane and that recovery time ranged from 2 to 40 days depending on characteristics such as gender or income. Findings suggest that insights from transaction data could be used to target emergency response and to estimate economic loss at local level in the wake of a disaster.
This document proposes a method to quantify the political leaning of Twitter users based on their tweet and retweet activity. It formulates the inference of political leaning as a convex optimization problem that incorporates two ideas: (1) a user's tweets and retweets should be consistent in sentiment, and (2) similar users tend to be retweeted by similar audiences. The method is evaluated on 119 million election-related tweets from the 2012 US presidential election and achieves 94% accuracy in classifying frequently retweeted sources. A quantitative analysis of the tweets also finds that parody accounts and less vocal users are more likely to be liberal, while hashtags usage changes significantly with political events.
This document discusses bridging the gap between federal Web 2.0 capabilities and local needs during major disasters. It notes that while emergency management is using social media for information dissemination, it has not fully utilized Web 2.0 technologies like facial recognition and responder coordination. The research aims to assess how often state and local entities request federal Web 2.0 expertise during disasters and what capabilities would help emergency management. It hypothesizes that incorporating Web 2.0 teams into an Emergency Support Function could facilitate resource sharing between levels of government. The literature review finds that citizens' social media use exceeds emergency management's utilization of Web 2.0 technologies.
An Overview on the Use of Data Mining and Linguistics Techniques for Building...ijcsit
The usage of Online Social Networks (OSN), such as Facebook and Twitter are becoming more and more
popular in order to exchange and disseminate news and information in real-time. Twitter in particular
allows the instant dissemination of short messages in the form of microblogs to followers. This Survey
reviews literature to explore and examine the usage of how OSNs, such as the microblogging tool Twitter,
can help in the detection of spreading epidemics. The paper highlights significant challenges in the field of
Natural Language Processing (NLP) when using microblog based Early Disease Detection Systems. For
instance, microblogging data is an unstructured collection of short messages (140 characters in Twitter),
with noise and non-standard use of the English language. Hence, research is currently exploring the field
of linguistics in order to determine the semantics of the text and uses data mining techniques in order to
extract useful information for disease spread detection. Furthermore, the survey discusses applications and
existing early disease detection systems based on OSNs and outlines directions for future research on
improving such systems based on a combination of linguistics methods, data mining techniques and
recommendation systems.
Public Health Crisis Analytics for Gender ViolenceHemant Purohit
The document discusses using social media data to analyze gender-based violence campaigns and public attitudes. It summarizes a study of cross-campaign participation on Twitter around three hashtags. Most users and tweets were individual rather than organizational. Few male users were observed. The document also describes a system called CitizenHelper for visualizing attitude trend analytics over time from social media to evaluate campaign effects and inform intervention events.
This paper examines digital literacy and how it relates to the philosophical study of ignorance. Ignorance of how digital technologies work (e.g. how users’ online activities can be used to the advantage of platform owners without the users’ knowledge, and how browsing can be confined) is still not well understood from the perspective of user practice.
Based on the following Special Issue of Teaching in Higher Education: https://doi.org/10.1080/13562517.2018.1547276
Talk done at Lancaster University, Edinburgh University, the SRHE conference, Sussex University,
The document discusses the United States' current cyber strategy and whether it supports offensive cyber operations. It analyzes several scholarly articles on cyber warfare doctrine and strategy. While the articles provide examples of states conducting offensive cyber attacks, the document's hypothesis is that the US cyber strategy focuses on defense and does not explicitly support offensive computer network attacks to achieve national security objectives. The purpose is to examine US cyber strategy and determine if it should incorporate offensive operations to help achieve national goals.
This document provides an overview of intelligence analysis. It discusses how intelligence analysts must tell decision makers what they know, what they don't know, and then their thoughts, keeping those separate. The analysis of information involves turning disparate facts into focused conclusions. Intelligence analysis applies cognitive methods to assess data and test assumptions while detecting deceptions to reduce ambiguity. Structured analytical techniques have been used more since 9/11 to better manage analysis and align it with scientific principles. A common analysis technique involves using social networking data to map networks and identify important nodes.
Predictive policing uses mathematical and analytical techniques to identify potential criminal activity based on data collection and analysis of past crime trends. Law enforcement agencies collect data on repeat offenders, victims, and crime locations to analyze criminal patterns and make predictions about where increased police presence may be needed to prevent future crimes. The effectiveness of these strategies is then reevaluated to improve methods for reducing criminal activity.
Intelligence services are currently focusing on the fight against terrorism, leaving relatively little resources to monitor other security threats. For this reason, they often ignore external information activities that do not pose immediate threats to their government's interests. Extremely few external services operate globally. Almost all other services focus on immediate neighbors or regions. These services usually depend on relationships with these global services for information on areas beyond their immediate neighborhoods, and often sell their regional expertise for what they need globally. A feature of both internal and external services is that they behave like a caste.
DOI: 10.13140/RG.2.2.25847.68006
Gabrielle HetlandAlthough the United States has a very stron.docxhanneloremccaffery
Gabrielle Hetland
Although the United States has a very strong and effective intelligence community, there are several unavoidable challenges that set back some of the processes and hinders the intelligence community from working to its full potential. The most important challenges that I see include flow of information, civil liberties and secrecy.
Since the United States does not have one large domestic intelligence agency that completes all intelligence-related tasks, it is much more difficult for them to be able to transfer information to the right people in a timely manner. I think it is very beneficial that we are able to have such a wide variety of intelligence agencies, each with a specific mission set so subject matter experts can focus on their mission to the best of their abilities, however, on the flip side, many of them have to jump through hoops to get additional information on certain subjects or track down the originator of a product. Having so many different agencies requires a lot more work to get a good flow of communication between the agencies and a lot of valuable information can be lost in the process.
Civil liberties always has and always will be a major challenge for the intelligence community. In order to do their job effectively, intelligence personnel need to be able to conduct surveillance around the clock. Especially in today’s world, people do not want their rights to private taken away, making this jobs very difficult for intelligence and law enforcement personnel. With the rise of domestic terrorism and homegrown extremists, the IC will continue to need increased access in to people’s lives and workplace in order to detect these criminals and prevent future activity.
Lastly, secrecy has been a major challenge to the IC because much of the information dealt with is classified and needs to remain a secret for national security concerns, however, people do not want information kept from there. It is difficult to determine what information should be released to the public to ensure their safety while at the same time, not disrupting an operation. I think the IC has done everything right so far in regards to these issues. There is really no way to fix these challenges while at the same time maintain the high level of national security that we have.
Resources:
Aftergood, S. (1996). Three categories of secrecy. Secrecy and accountability in U.S. intelligence. Federation of American Scientists. Retrieved from https://www.hsaj.org/articles/147
Burch, J. (2007). A domestic intelligence agency for the United States? A comparative analysis of domestic intelligence agencies and their implications for homeland security. Homeland Security Affairs 3, 2. Retrieved from https://www.hsaj.org/articles/147
Office of the Director of National Intelligence. (n.d.). Organization. Retrieved from http://www.dni.gov/index.php/about/organization
Marissa Austin
Intelligence is the act of sound understanding, planning, ...
The document discusses building trust-based social networks to help address issues of information overload faced by intelligence analysts. It proposes creating a system called METIS to allow intelligence analysts, government departments, NGOs, and contractors to interact online prior to deployment. This could help build relationships and trust to facilitate information sharing in the field. The system would use recommendation algorithms and track user trust levels and expertise to help analysts quickly find relevant information from across different sources. However, challenges remain in designing algorithms that can properly assess and utilize trust in this high-risk domain.
disinformation risk management: leveraging cyber security best practices to s...Sara-Jayne Terp
This document discusses leveraging cybersecurity best practices to support cognitive security goals related to disinformation and misinformation. It outlines three layers of security - physical, cyber, and cognitive security. It then provides examples of cognitive security risk assessment and mapping the risk landscape. Next, it discusses working together to mitigate and respond to risks through proposed cognitive security operations centers. Finally, it provides a hypothetical example of conducting a country-level risk assessment and designing a response strategy. The document advocates adapting frameworks and standards from cybersecurity to help conceptualize and coordinate cognitive security challenges and responses.
Helping Crisis Responders Find the Informative Needle in the Tweet HaystackCOMRADES project
Leon Derczynski - University of Sheffield,
Kenny Meesters - TU Delft, Kalina Bontcheva - University of Sheffield, Diana Maynard- University of Sheffield
WiPe Paper – Social Media Studies
Proceedings of the 15th ISCRAM Conference – Rochester, NY, USA May 2018
Big data analytics: from threatening privacy to challenging democracySamos2019Summit
Big data analytics pose threats to individual and group privacy that can undermine key aspects of democracy. The use of big data for political targeting and messaging allows extensive profiling, prediction of views and behaviors, and manipulation of opinions. Over time, this can fragment political messages, obstruct open debate, and chill political expression through surveillance and the risk of being inaccurately profiled. Protecting privacy is important for maintaining fair elections and pluralism of ideas.
There are numerous ways to analyse the web information, generally web substance are housed in
large information sets and basic inquiries are utilized to parse such information sets. As the requests
expanded with time, mining web information amended to meet challenging task in a web analysis.
Machine learning methodologies are the most up to date one to go into these analysis forms. Different
approaches like decision trees, association rules, Meta heuristic and basic learning methods are embraced
for making web data appraisal and mining data from various web instances. This study will highlight these
approaches in perspective of web investigation. One of the prime goals of this exploration is to investigate
more data mining approaches alongside machine learning systems, and to express emerging collaboration
of web analytics with artificial intelligence.
Data-Mining Twitter for Political Science -Hickman, Alfredo - Honors ThesisAlfredo Hickman
This thesis examines the creation of a data mining system to extract, process, and analyze tweets from Twitter for use in political science research. The author builds an information system that collects Twitter data in real-time from a random list of 279 Members of Congress. The tweets and accompanying metadata are analyzed to provide insights into political behavior and discourse. By studying uncensored political discussions online, researchers can better understand important issues, how information spreads, and identify political networks. Analyzing social media can advance understanding of government communication and enhance research on political deliberation.
Human Trafficking-A Perspective from Computer Science and Organizational Lead...Turner Sparks
This document discusses using an interdisciplinary approach to address the issue of human trafficking. It focuses on how perspectives from computer science and organizational leadership can help law enforcement utilize surveillance and tracking software. The author conducted a literature review and found that better software for facial recognition and human tracking could be developed. However, current technology works best in controlled environments and laws need to regulate privacy issues related to increased video surveillance. Overall, the document argues that further advancing surveillance technology and providing more training to law enforcement on human trafficking should be priorities to help solve this problem.
Social Media play a critical role during crisis events, revealing a natural coordination dynamic. We propose a computational framework guided by social science principles to measure, analyze, and understand coordination among the different types of organizations and actors in crisis response. The analysis informs both the scientific account of cooperative behavior and the design of applications and protocols to support crisis management.
H. Purohit, A. Hampton, V. Shalin, A. Sheth, J. Flach. Framework to Analyze Coordination in Crisis Response. Workshop on Collaboration and Crisis Informatics, CSCW-2012.
http://knoesis.wright.edu/library/resource.php?id=1640
Clustering analysis on news from health OSINT data regarding CORONAVIRUS-COVI...ALexandruDaia1
Our primarly goal was to detect clusters via gensim libraries in news data consisting ofinformation regarding health and threats. We identified clusters for the periodscorresponding: i) Jannuary 2006 until the end of 2019, as December 2019 is considered thefirst month in which information about CORONVIRUS COVID-19 was made public; ii)between the 1st of Jannuary 2019 and 31st December 2019; and iii) between the 31st ofDecember 2019 and the 14th of April 2020. We conducted experiments using naturallanguage on open source intelligence data offered generously by brica.de, a providerspecialized in Business Risk Intelligence & Cyberthreat Awareness.
The document summarizes challenges facing the Department of Homeland Security (DHS) in acquiring and applying national intelligence. It notes that while DHS has made progress, it still struggles with issues like properly classifying critical infrastructure and prioritizing security efforts. The literature suggests DHS should adopt a risk-based approach to identify the most critical facilities and assess potential threats, rather than treating all infrastructure as equally important. This would help DHS focus its resources on the most significant security risks facing the United States.
IRJET - Political Orientation Prediction using Social Media ActivityIRJET Journal
This document discusses research into predicting the political orientation of Twitter users based on their social media activity. The researchers aim to incorporate factors like tweets, retweets, followers, followees, and network connections to better understand how political views are expressed and shaped on Twitter. Prior studies that have analyzed political bias in media outlets and the spread of information across partisan networks on social media are reviewed. The researchers describe collecting and analyzing Twitter data including tweets, retweets, mentions, followers and who a user follows to predict individual users' political leanings.
Using Financial Transaction Data To Measure Economic Resilience To Natural Di...UN Global Pulse
This project explored how financial transaction data can be analysed to better understand the economic resilience of people affected by natural disasters. The project used the Mexican state of Baja California Sur as a case study to assess the impact of Hurricane Odile on livelihoods and economic activities over a period of six months in 2014. The project measured daily Point of Sale transactions and ATM withdrawals at high geospatial resolution to gain insight into the way people prepare for and recover from disaster.
The study revealed that people spent 50% more than usual on items such as food and gasoline in preparation for the hurricane and that recovery time ranged from 2 to 40 days depending on characteristics such as gender or income. Findings suggest that insights from transaction data could be used to target emergency response and to estimate economic loss at local level in the wake of a disaster.
This document proposes a method to quantify the political leaning of Twitter users based on their tweet and retweet activity. It formulates the inference of political leaning as a convex optimization problem that incorporates two ideas: (1) a user's tweets and retweets should be consistent in sentiment, and (2) similar users tend to be retweeted by similar audiences. The method is evaluated on 119 million election-related tweets from the 2012 US presidential election and achieves 94% accuracy in classifying frequently retweeted sources. A quantitative analysis of the tweets also finds that parody accounts and less vocal users are more likely to be liberal, while hashtags usage changes significantly with political events.
This document discusses bridging the gap between federal Web 2.0 capabilities and local needs during major disasters. It notes that while emergency management is using social media for information dissemination, it has not fully utilized Web 2.0 technologies like facial recognition and responder coordination. The research aims to assess how often state and local entities request federal Web 2.0 expertise during disasters and what capabilities would help emergency management. It hypothesizes that incorporating Web 2.0 teams into an Emergency Support Function could facilitate resource sharing between levels of government. The literature review finds that citizens' social media use exceeds emergency management's utilization of Web 2.0 technologies.
An Overview on the Use of Data Mining and Linguistics Techniques for Building...ijcsit
The usage of Online Social Networks (OSN), such as Facebook and Twitter are becoming more and more
popular in order to exchange and disseminate news and information in real-time. Twitter in particular
allows the instant dissemination of short messages in the form of microblogs to followers. This Survey
reviews literature to explore and examine the usage of how OSNs, such as the microblogging tool Twitter,
can help in the detection of spreading epidemics. The paper highlights significant challenges in the field of
Natural Language Processing (NLP) when using microblog based Early Disease Detection Systems. For
instance, microblogging data is an unstructured collection of short messages (140 characters in Twitter),
with noise and non-standard use of the English language. Hence, research is currently exploring the field
of linguistics in order to determine the semantics of the text and uses data mining techniques in order to
extract useful information for disease spread detection. Furthermore, the survey discusses applications and
existing early disease detection systems based on OSNs and outlines directions for future research on
improving such systems based on a combination of linguistics methods, data mining techniques and
recommendation systems.
Public Health Crisis Analytics for Gender ViolenceHemant Purohit
The document discusses using social media data to analyze gender-based violence campaigns and public attitudes. It summarizes a study of cross-campaign participation on Twitter around three hashtags. Most users and tweets were individual rather than organizational. Few male users were observed. The document also describes a system called CitizenHelper for visualizing attitude trend analytics over time from social media to evaluate campaign effects and inform intervention events.
This paper examines digital literacy and how it relates to the philosophical study of ignorance. Ignorance of how digital technologies work (e.g. how users’ online activities can be used to the advantage of platform owners without the users’ knowledge, and how browsing can be confined) is still not well understood from the perspective of user practice.
Based on the following Special Issue of Teaching in Higher Education: https://doi.org/10.1080/13562517.2018.1547276
Talk done at Lancaster University, Edinburgh University, the SRHE conference, Sussex University,
The document discusses the United States' current cyber strategy and whether it supports offensive cyber operations. It analyzes several scholarly articles on cyber warfare doctrine and strategy. While the articles provide examples of states conducting offensive cyber attacks, the document's hypothesis is that the US cyber strategy focuses on defense and does not explicitly support offensive computer network attacks to achieve national security objectives. The purpose is to examine US cyber strategy and determine if it should incorporate offensive operations to help achieve national goals.
This document provides an overview of intelligence analysis. It discusses how intelligence analysts must tell decision makers what they know, what they don't know, and then their thoughts, keeping those separate. The analysis of information involves turning disparate facts into focused conclusions. Intelligence analysis applies cognitive methods to assess data and test assumptions while detecting deceptions to reduce ambiguity. Structured analytical techniques have been used more since 9/11 to better manage analysis and align it with scientific principles. A common analysis technique involves using social networking data to map networks and identify important nodes.
Predictive policing uses mathematical and analytical techniques to identify potential criminal activity based on data collection and analysis of past crime trends. Law enforcement agencies collect data on repeat offenders, victims, and crime locations to analyze criminal patterns and make predictions about where increased police presence may be needed to prevent future crimes. The effectiveness of these strategies is then reevaluated to improve methods for reducing criminal activity.
Intelligence services are currently focusing on the fight against terrorism, leaving relatively little resources to monitor other security threats. For this reason, they often ignore external information activities that do not pose immediate threats to their government's interests. Extremely few external services operate globally. Almost all other services focus on immediate neighbors or regions. These services usually depend on relationships with these global services for information on areas beyond their immediate neighborhoods, and often sell their regional expertise for what they need globally. A feature of both internal and external services is that they behave like a caste.
DOI: 10.13140/RG.2.2.25847.68006
Gabrielle HetlandAlthough the United States has a very stron.docxhanneloremccaffery
Gabrielle Hetland
Although the United States has a very strong and effective intelligence community, there are several unavoidable challenges that set back some of the processes and hinders the intelligence community from working to its full potential. The most important challenges that I see include flow of information, civil liberties and secrecy.
Since the United States does not have one large domestic intelligence agency that completes all intelligence-related tasks, it is much more difficult for them to be able to transfer information to the right people in a timely manner. I think it is very beneficial that we are able to have such a wide variety of intelligence agencies, each with a specific mission set so subject matter experts can focus on their mission to the best of their abilities, however, on the flip side, many of them have to jump through hoops to get additional information on certain subjects or track down the originator of a product. Having so many different agencies requires a lot more work to get a good flow of communication between the agencies and a lot of valuable information can be lost in the process.
Civil liberties always has and always will be a major challenge for the intelligence community. In order to do their job effectively, intelligence personnel need to be able to conduct surveillance around the clock. Especially in today’s world, people do not want their rights to private taken away, making this jobs very difficult for intelligence and law enforcement personnel. With the rise of domestic terrorism and homegrown extremists, the IC will continue to need increased access in to people’s lives and workplace in order to detect these criminals and prevent future activity.
Lastly, secrecy has been a major challenge to the IC because much of the information dealt with is classified and needs to remain a secret for national security concerns, however, people do not want information kept from there. It is difficult to determine what information should be released to the public to ensure their safety while at the same time, not disrupting an operation. I think the IC has done everything right so far in regards to these issues. There is really no way to fix these challenges while at the same time maintain the high level of national security that we have.
Resources:
Aftergood, S. (1996). Three categories of secrecy. Secrecy and accountability in U.S. intelligence. Federation of American Scientists. Retrieved from https://www.hsaj.org/articles/147
Burch, J. (2007). A domestic intelligence agency for the United States? A comparative analysis of domestic intelligence agencies and their implications for homeland security. Homeland Security Affairs 3, 2. Retrieved from https://www.hsaj.org/articles/147
Office of the Director of National Intelligence. (n.d.). Organization. Retrieved from http://www.dni.gov/index.php/about/organization
Marissa Austin
Intelligence is the act of sound understanding, planning, ...
The document discusses building trust-based social networks to help address issues of information overload faced by intelligence analysts. It proposes creating a system called METIS to allow intelligence analysts, government departments, NGOs, and contractors to interact online prior to deployment. This could help build relationships and trust to facilitate information sharing in the field. The system would use recommendation algorithms and track user trust levels and expertise to help analysts quickly find relevant information from across different sources. However, challenges remain in designing algorithms that can properly assess and utilize trust in this high-risk domain.
What does “BIG DATA” mean for official statistics?Vincenzo Patruno
In our modern world more and more data are generated on the web and produced by sensors in the ever growing number of electronic devices surrounding us. The amount of data and the frequency at which they are produced have led to the concept of 'Big data'. Big data is characterized as data sets of increasing volume, velocity and variety; the 3 V's. Big data is often largely unstructured, meaning that it has no pre-defined data model and/or does not fit well into conventional relational databases.
The Importance Of Intelligence-Led PolicingMelissa Dudas
The document discusses the importance of intelligence-led policing for modern law enforcement agencies. As this concept has shaped policing, the need for intelligence analysts has grown. Analysts must have research, analytical, critical thinking, and communication skills to effectively interpret data and disseminate timely intelligence. Community policing and intelligence-led policing can complement each other by helping gather more intelligence than using just one strategy alone. Gathering intelligence about communities is important for productive community relations and counter-terrorism efforts.
Big Data & Privacy -- Response to White House OSTPMicah Altman
Big data has huge implications for privacy, as summarized in our commentary below:
Both the government and third parties have the potential to collect extensive (sometimes exhaustive), fine grained, continuous, and identifiable records of a person’s location, movement history, associations and interactions with others, behavior, speech, communications, physical and medical conditions, commercial transactions, etc. Such “big data” has the ability to be used in a wide variety of ways, both positive and negative. Examples of potential applications include improving government and organizational transparency and accountability, advancing research and scientific knowledge, enabling businesses to better serve their customers, allowing systematic commercial and non-commercial manipulation, fostering pervasive discrimination, and surveilling public and private spheres.
On January 23, 2014, President Obama asked John Podesta to develop in 90 days, a 'comprehensive review' on big data and privacy.
This lead to a series of workshop on big data and technology at MIT, and on social cultural & ethical dimensions at NYU, with a third planned to discuss legal issues at Berkeley. A number of colleagues from our Privacy Tools for Research project and from the BigData@CSAIL projects have contributed to these workshops and raised many thoughtful issues (and the workshop sessions are online and well worth watching).
My colleagues at the Berkman Center, David O'Brien, Alexandra Woods, Salil Vadhan and I have submitted responses to these questions that outline a broad, comprehensive, and systematic framework for analyzing these types of questions and taxonomize a variety of modern technological, statistical, and cryptographic approaches to simultaneously providing privacy and utility. This comment is made on behalf of the Privacy Tools for Research Project, of which we are a part, and has benefitted from extensive commentary by the other project collaborators.
150 words agree or disagreeFuture Criminal Intelligence Enviro.docxdrennanmicah
150 words agree or disagree
Future Criminal Intelligence Environment:
It might seem that the criminal environment has not changed, as both personal and property crimes are the part of everyday routine of law enforcement. At the same time, technological development has provided new possibilities for criminals by allowing them to steal and commit fraud at bigger scale. Future criminal intelligence environment will revolve around technologies, virtual space, and ICT. According to the current trends, high-tech crimes are growing exponentially with the inability of law enforcement to prevent or address them at once (Zavrsnik, 2010). According to the analysis of cybercrime worldwide, investigation of cybercrime has multiple barriers, including the lack of correspondence among different international agencies concerning the legal prosecution, limited number of skilled talent in law enforcement, and absence of effective methods that would allow to find and prosecute offenders (Brown, 2015). As a result, the criminals continue committing identity thefts, spreading dangerous viruses (e.g. ransomware), phishing, and hacking. Since the technologies will continue to improve and update, it is more likely that the criminals will alter their tactics. The main goal of the modern law enforcement is to prepare for the future tendencies by investing in cybercrime department, training talent, and researching the newest trends in cybercrime. Since this type of crime threatens the individual citizens as well as the entire countries, the law enforcement agencies must ensure that the organized crime does not feel comfortable in the virtual space, which can be observed today.
Intelligence Analytics:
Tools and techniques in intelligence analysis might vary across the analysts, systems, and countries. Since today analysts deal with the intelligence presented in a variety of forms, including the digital one, the methods of analysis can be different. For example, basic analytical process usually includes the following steps: collect and sift all available data, construct a preliminary diagram, evaluate new information in light of old data, collect further information, develop preliminary inferences, develop conclusions, assemble a report (United Nations, 2011). This structure can vary according to the available intelligence, protocol of assembling the data, and the scheme used by a specific agency. Several basic techniques of data analysis include event charting, link, flow, and telephone analyses (Berlusconi et al., 2016). These methods are used according to the specific events, goals, and available data. Several software are used today to analyze intelligence and information, including Law Enforcement Specific GIS, RMC and CAD information exchange. Analysis is more effective if the officers have a wide variety of data. For example, today, the agencies can use social media analysis as one of the effective tools in data mining. For instance, a research exploring inte.
Running head surveillance state research1 page 2runningSHIVA101531
This document contains three articles about state surveillance. The first article discusses China's extensive surveillance system using facial recognition and security cameras, which has been criticized by other nations. The second article discusses how governments have adopted technological surveillance of citizens during the COVID-19 pandemic to monitor compliance with public health laws and regulations. The third article argues that widespread digital surveillance is already occurring through devices like phones, TVs and IoT devices that can listen to conversations without users' knowledge, compromising privacy.
This document discusses the ethical issues surrounding governments using big data analysis to identify possible terrorist threats. It examines factors that determine whether such use is acceptable, including minimizing privacy intrusions, manipulation of data, and ensuring accuracy. While big data can help counter terrorism through identifying threats, its use also brings risks like overreach, false alarms, and lack of transparency that must be addressed. The line between ethical and unethical use depends on balancing security needs with preventing harm and protecting civil liberties.
This interview summarizes the work of UN Global Pulse, an initiative that explores how big data and real-time analytics can help with sustainable development efforts. The director, Robert Kirkpatrick, discusses Global Pulse's mission to accelerate the use of data science to protect populations from shocks. They derive data from sources like social media, mobile phone metadata, and other digital traces to gain insights into issues like food security, public health, and economic trends. Kirkpatrick highlights challenges like building analytical capacity, maintaining responsible data partnerships, and addressing issues of data access and privacy at scale. He provides examples of projects in Indonesia that use social media to study food prices and vulnerabilities.
This document provides an overview of a research project examining intimate partner violence (IPV) among young people ages 12-24 in Belize, with an emphasis on cyber abuse. The researchers conducted a literature review on existing studies related to gender-based violence, bullying, and healthy relationships. They then administered an online survey to 59 young people and held a focus group with 4 young adults to understand their views and experiences related to dating, IPV, and cyber abuse. The methodology section outlines the mixed methods research design using qualitative and quantitative data collection and analysis. The research aimed to answer questions about perceptions of IPV and healthy relationships among youth, as well as understanding of cyber-based gender violence.
Information Literacy: ‘Medicine’ in Improving Ways of Managing Information Ex...inventionjournals
We are now living in the information society and global village of which we are bombarded with huge sums of information which is not all relevant to us. It is therefore imperative to be well equipped with information literacy skills so as to curb the information explosion. Simply being exposed to a great deal of information will not make people informed citizens, they need information literacy skills. Information literacy comes as a ‘medicine’ in curing the information exposition. Information seekers can tackle information explosion by employing strategies such as information literacy education, development of information search skills, library education, user orientation, bibliographic user instruction, information fluency and all other information literacy competencies.
Case Study RubricCriterionStrongAverageWeakInt.docxketurahhazelhurst
Case Study Rubric
Criterion
Strong
Average
Weak
Introduction / Primary Problem, Issue or Question Identification
States the case objective and clearly defines the problem, issue or question
Minimally describes the case, includes only the problem, issue or question
Bypasses the introduction and moves directly to commentary on the case
Understanding of Primary Problem, Issue or Question
Identifies and demonstrates a sophisticated understanding of the primary issues and or problems in the case study
Identifies and demonstrates an accomplished understanding of most of the issues/problems
Identifies and demonstrates acceptable understanding of some of the issues/problems in the case study
Analysis and Evaluation of Issues/Problems
Presents an insightful and thorough analysis of all identified problems, issues or questions; includes all necessary calculations
Presents a thorough analysis of most of the problems, issues or questions identified; missing some necessary calculations
Presents a superficial or incomplete analysis of some of the identified problems, issues or questions; omits necessary calculations
Recommendations on Effective
Solution
s/Strategies
Supports diagnosis and opinions with convincing arguments and evidence; presents a balanced and critical view; interpretation is both reasonable and objective
. Recommendations logically supported
Supports diagnosis and opinions with limited reasoning and evidence; presents a one‐sided argument; demonstrates little engagement with ideas presented. Illogical recommendations
Little or no action suggested, and/or ineffective or disconnected solutions proposed to the issues in the case study. No attempt at logical support for recommendations
Links to Course Readings and Additional Research
Makes appropriate and powerful connections between identified issues/problems and the strategic concepts studied in the course readings and lectures; supplements case study with relevant and thoughtful research and identifies all sources of information
Makes appropriate but vague connections between identified issues/problems and concepts studied in readings and lectures; demonstrates limited command of the analytical tools studied; supplements case study with limited sources
Makes ineffective connections or shows no connection between issues identified and the concepts studied in the readings; supplements case study, if at all, with incomplete information and sources
Writing Mechanics and Formatting Guidelines
Demonstrates a clear understanding of the audience for the case. Utilizes formatting, clarity and structure to enable the audience to readily see and understand recommended actions. Writing is logical, grammatically correct, spelling is error free
Demonstrates a limited understanding of the audience for the case. Ineffective structuring of response making it difficult to readily see and understand recommended actions. Writing shows poor logic, grammatical and spelli ...
Information Gathering in Intelligence AgenciesNora A. Rahim
Information gathering and sharing between agencies is critical for preventing threats like terrorism, yet involvement of classified information makes studying the relationship between information science and intelligence work difficult. The document discusses the differences between information and intelligence, the intelligence cycle of collecting, analyzing and using information to produce finished intelligence for policymakers, and various types of intelligence including current, estimative, warning, research, and scientific/technical intelligence. It concludes by recommending better information retrieval and an understanding of information science to provide timely intelligence while reducing pressure on analysts.
Information Sharing, Dot Connecting and Intelligence Failures.docxannettsparrow
Information Sharing, Dot Connecting and Intelligence Failures:
Revisiting Conventional Wisdom
By
Russell Travers
Deputy Director, Information Sharing and Knowledge Development
National Counterterrorism Center
This paper, written in August 2009, was submitted to the Director of National Intelligence
2009 Galileo Awards Program. The Galileo Awards Program is an annual Intelligence
Community-wide competition designed to encourage and recognize innovative workforce
ideas that address current challenges and help shape the future of U.S. Intelligence.
All statements of fact, opinion, or analysis expressed are those of the author and do not
reflect the official positions or views of the National Counterterrorism Center (NCTC) or
any other U.S. Government agency. Nothing in the contents should be construed as
implying U.S. Government or NCTC endorsement of the author’s views. This material has
been reviewed to prevent the disclosure of classified information.
The year is 2014. The Intelligence Community is ten years into its efforts to
implement the Intelligence Reform and Terrorism Prevention Act (IRTPA). While
change has been evident on many fronts, nothing was more closely identified with
intelligence reform than information sharing; ever since the 9/11 Commission
declared that “the biggest impediment to all-source analysis – to a greater
likelihood of connecting the dots – is the human or systemic resistance to sharing
information”1, the two had been inextricably linked. And while we were pushing
more electrons than ever before, dissatisfaction continued: in 2014, as in 2009,
no analyst in the IC had effective access to all information; analysts in many parts
of the Community complained that they couldn’t get operational traffic or law
enforcement information; we had little ability to do large scale processing of
foreign and domestic data sets; our non Federal partners were still dissatisfied
with the quality of information sharing. A dizzying array of directives had been
issued. Arbitration procedures had been established. And yet organizations
weren’t getting the information they claimed to “need.” Legitimate issues
coexisted with tripe. According to the critics, we still couldn’t connect those dots.
The reality, however, was far more complex: the only question was whether it
took a major intelligence failure to realize that fact.
This is the path we’re on. We will continue to hear claims that information sharing has
“barely improved since 9/11.” Such hyperbole is unmitigated nonsense. The robust sharing of
information between and among the key organizations has undoubtedly contributed to the fact
that we haven’t suffered a major attack. And by any objective standard, the level of sharing
1 The 9/11 Commission Report: Final Report of the National Commission on Terrorist Attacks Upon the United
States; U.S. Government Print.
The document discusses a proposal for an information professional to help improve Kapco Adhesive Product Company's data management. Kapco operates under four sections without centralized information management, negatively impacting productivity and sales. The proposal outlines solutions like creating metadata for products, digital archives, an online safety portal, and patent/research organization. It provides a budget and timeline for initial assessment, implementation, future support, and completion within 4-8 weeks. Hiring an information professional would benefit Kapco through evidence-based practices and improved efficiency.
This document provides a checklist for evaluating the validity of news articles. It lists topics to consider such as checking the source and date of an article, reading beyond the headlines, verifying supporting sources, and checking for biases. The checklist helps determine the level of fake news, from satire to completely fabricated content, and asks for a final conclusion on the article's validity supported by the information collected.
This lesson plan spans 5-6 class periods and teaches high school students how to identify fake news. It begins by showing video clips about fake news and having students discuss how manipulating the truth can impact society. Students are then introduced to different types of fake news and work in groups analyzing news articles. They participate in online games and activities to develop critical thinking skills for identifying authentic news. The lesson concludes with students creating their own fake news campaigns and presenting them to a panel. The goal is for students to understand how fake news can influence public perception and to develop skills in verifying the credibility of news.
The document summarizes the author's learning experience from an internship at an academic library. The internship allowed the author to apply skills learned in coursework and gain experience in activities like outreach, cataloging, and creating information literacy tutorials. While the internship focused more on some areas than others, like reference which was limited due to summer break, the author found the experience incredibly valuable overall for understanding library operations. The author also learned the importance of being thorough, not rushing projects, and asking for help from supervisors.
Information-Seeking Behaviors of Parents of Children with ADHD: Experiences, ...Laura Levy
Parents of children with ADHD often have unmet information needs when it comes to understanding and caring for their child's condition. This document discusses a study that aims to better understand the information seeking behaviors of these parents. It reviews literature showing that parents generally seek information from healthcare providers, the internet, peer groups and organizations. However, barriers like limited internet access, low health literacy and an inability to understand technical research can make finding reliable information difficult. The proposed study would survey parents of ADHD children about their confidence in and sources of information. It would also interview some parents to learn about how their information needs have changed at different stages of their child's diagnosis and care, using a model of progressive information seeking situations. The goal is
The document describes a metadata schema assignment for a puppetry collection. It includes instructions to design a metadata element set for the collection with 10-15 elements. The student proposes elements such as Puppet Name, Description, Date, Cast, Relationship, Title, Type, Puppet Type, Identifier, Rights, Subject, and Creator. Guidelines and examples are provided for each element. The metadata set is designed for a puppetry collection at Jim Henson's Creature Shop to support finding and identifying puppets.
The document discusses plagiarism and defines it as presenting another's ideas or work as one's own without proper citation or credit. It notes that NEOMED considers plagiarism a form of academic misconduct. The document also includes an infographic from Turnitin that outlines different types of plagiarism on a spectrum from copying word-for-word to properly citing sources but relying too closely on the original work.
This document provides tips for searching medical databases, including using controlled vocabularies, boolean operators, and popular journal article databases. It recommends using quotation marks around search terms and boolean operators like AND, OR, and NOT to narrow or broaden results. Controlled vocabularies like MeSH, CINAHL Thesaurus, and PsycINFO Thesaurus can help effectively search databases by describing article subjects. Popular databases mentioned are Cochrane Library, PubMed, CINAHL Plus, MEDLINE, Web of Science, and PsycINFO.
Laura Levy has experience as a teacher, library assistant, and intern. She has a B.S. in Interdisciplinary Studies with a concentration in Elementary Education from Old Dominion University, a M.Ed. in Elementary Education from Old Dominion University, and a M.L.I.S. from Old Dominion University. Her experience includes working as a front desk graduate assistant at Kent State University Fashion Library, a graduate student assistant at Kent State University Libraries providing customer support and website maintenance, and an intern at Northeast Ohio Medical University where she created tutorials and cataloged materials. She also has experience as a 5th grade and 4th grade classroom teacher.
This document provides a tutorial on using the biomedical literature database PubMed. It begins with an overview of PubMed, explaining that it contains over 27 million citations and is maintained by the U.S. National Library of Medicine. The tutorial then covers various topics for searching PubMed effectively such as using controlled vocabularies, Boolean operators, field tags, and filters. It also discusses accessing full text articles and getting help via library contacts or additional PubMed resources. The overall aim is to teach researchers how to search PubMed and retrieve relevant citations for their topics of interest.
Strategies for Effective Upskilling is a presentation by Chinwendu Peace in a Your Skill Boost Masterclass organisation by the Excellence Foundation for South Sudan on 08th and 09th June 2024 from 1 PM to 3 PM on each day.
This presentation was provided by Steph Pollock of The American Psychological Association’s Journals Program, and Damita Snow, of The American Society of Civil Engineers (ASCE), for the initial session of NISO's 2024 Training Series "DEIA in the Scholarly Landscape." Session One: 'Setting Expectations: a DEIA Primer,' was held June 6, 2024.
A workshop hosted by the South African Journal of Science aimed at postgraduate students and early career researchers with little or no experience in writing and publishing journal articles.
Main Java[All of the Base Concepts}.docxadhitya5119
This is part 1 of my Java Learning Journey. This Contains Custom methods, classes, constructors, packages, multithreading , try- catch block, finally block and more.
A Strategic Approach: GenAI in EducationPeter Windle
Artificial Intelligence (AI) technologies such as Generative AI, Image Generators and Large Language Models have had a dramatic impact on teaching, learning and assessment over the past 18 months. The most immediate threat AI posed was to Academic Integrity with Higher Education Institutes (HEIs) focusing their efforts on combating the use of GenAI in assessment. Guidelines were developed for staff and students, policies put in place too. Innovative educators have forged paths in the use of Generative AI for teaching, learning and assessments leading to pockets of transformation springing up across HEIs, often with little or no top-down guidance, support or direction.
This Gasta posits a strategic approach to integrating AI into HEIs to prepare staff, students and the curriculum for an evolving world and workplace. We will highlight the advantages of working with these technologies beyond the realm of teaching, learning and assessment by considering prompt engineering skills, industry impact, curriculum changes, and the need for staff upskilling. In contrast, not engaging strategically with Generative AI poses risks, including falling behind peers, missed opportunities and failing to ensure our graduates remain employable. The rapid evolution of AI technologies necessitates a proactive and strategic approach if we are to remain relevant.
Assessment and Planning in Educational technology.pptxKavitha Krishnan
In an education system, it is understood that assessment is only for the students, but on the other hand, the Assessment of teachers is also an important aspect of the education system that ensures teachers are providing high-quality instruction to students. The assessment process can be used to provide feedback and support for professional development, to inform decisions about teacher retention or promotion, or to evaluate teacher effectiveness for accountability purposes.
This slide is special for master students (MIBS & MIFB) in UUM. Also useful for readers who are interested in the topic of contemporary Islamic banking.
Azure Interview Questions and Answers PDF By ScholarHat
LIS 60030 Final Project
1. Running head: INFORMATION BEHAVIORS IN THE INTELLIGENCE COMMUNITY 1
Information Behaviors in the Intelligence Community
Laura Levy
Kent State University
2. INFORMATION BEHAVIORS IN THE INTELLIGENCE COMMUNITY 2
Information behaviors are unique to an individual and the information that the user is seeking.
One of the issues impacting information behaviors in today’s digital environment is that there is too much
information from too many sources. This overabundance of information causes information overload,
which can result in lower quality of work produced or a lack of focus by the information user. Too much
information can be overwhelming to anyone, but in certain situations information overload can have more
serious repercussions.
The Intelligence Community (IC) is one such group of information users that routinely
experiences information overload. Too much information can compromise the efficiency of the
information user in identifying threats and producing reports in a timely and accurate manner.
Intelligence analysts need a solution to process the vast amounts of information that they are exposed to
each workday. Through a study of the literature related to the IC and the user information behaviors
found in the LIS field, a solution to handling information overload may be found in incorporating LIS
information behavior strategies into the Intelligence Cycle.
User Group Definition
The user group that this paper will focus on is the all-source intelligence analysts that work within
the United States intelligence community. According to the RAND Corporation (a nonprofit, nonpartisan
research organization), “the intelligence community comprises the many agencies and organizations
responsible for intelligence gathering, analysis, and other activities that affect foreign policy and national
security” (“Intelligence Community”, n.d.). Further, in the United States the IC can be subdivided on the
federal, state, and local level, all ideally sharing information amongst agencies.
The federal IC is comprised of 17 different agencies, divided into three separate groups that fall
under the supervision of the Office of the Director of National Intelligence (ODNI) and works in
cooperation with the Central Intelligence Agency. The armed forces IC is comprised of the Defense
Intelligence Agency, the National Geo-Spatial Intelligence Agency, the National Reconnaissance Office,
and the National Security Agency under the Services group. The various departments of the federal
government also have agencies concerned with Intelligence Analysis. These departments are the Drug
Enforcement Agency, the Department of Treasury, the Department of State, the Department of Energy,
the Department of Homeland Security, and the Federal Bureau of Investigation (Intelligence Community,
2015). These agencies all employ intelligence analysts in some capacity.
The federal IC works with the state and local governments through fusion centers located
throughout the United States. According to Gerardi (2013), “Congress has defined fusion centers as
collaborative effort of 2 or more Federal, State, local, or tribal government agencies that combines
resources, expertise, or information with the goal of maximizing the ability of such agencies to detect,
prevent, investigate, apprehend, and respond to criminal or terrorist activity” (Gerardi, p. 4). Fusions
centers emerged because of the attacks of 9/11 to prevent future acts of terrorism. The fusion centers are
intended to increase the federal intelligence capabilities related to domestic terrorism using local, state,
and tribal law enforcement (Gerardi, p. 1). Fusion centers are intended to compliment the Federal
agencies by providing additional intelligence information, but unfortunately the intent doesn’t match the
results.
3. INFORMATION BEHAVIORS IN THE INTELLIGENCE COMMUNITY 3
Real-Life Context of Users
While fusion centers and the Federal IC have the best intentions of creating a cohesive
intelligence network, they are failing due to information overload and lack of cohesion between the levels
of government and agencies. Inconsistent training also slows the process of analyzing important
intelligence information in the time that it is usually needed. While fusion centers are relatively new to
the intelligence field, the other agencies have existed for decades, which also leads to a disconnect
between governmental levels.
Information overload is one of the reasons why intelligence analysis is difficult to complete
effectively, and it occurs at all levels of the government. On the local and state level too much data
overloads the analysts, and coupled with other issues such as inadequate training, the ability to analyze
and act on information is significantly affected (Brueggemann, p. V). Information comes from a variety
of sources today, including social media, websites and traditional clandestine operations. The issue of
information overload negatively impacting the IC is not just located at the state and local level, it can be
found at the federal level as well. For example, the FBI frequently collects too much information and
can’t effectively decide what information is important in a timely manner (Brueggemann, p.6).
A 2012 Congressional investigation revealed findings that fusions centers provided subpar
intelligence, which wasn’t produced in a timely manner, and it was suggested that the work the fusion
centers performed was redundant. Most of the fusion centers lacked the proper training to provide
adequate intelligence, and those that did were unable to clearly communicate and share that information
to the federal agencies (Devine, p.6).
Theories, Models, and Approaches
All the problems mentioned in this report can be traced back to the way that the IC analysts
interact with information and their resulting behaviors. The information overload that is experienced can
be very stressful and lead to errors. The lack of accessibility to other IC agencies intelligence reports can
lead to analyst frustration and incomplete analysis. Information behavior theories found in the LIS field
of study could help improve the current situation that analysts find themselves in daily.
Intelligence analysts are often faced with overwhelming amounts of information and that causes
several negative outcomes in relation to the analyst and the analysis of a threat. Young (2013) explains
that the Intelligence Community is getting overrun with information and causes the analyst to lose sight
of what is important, which may result in important information being ignored (Young, p. 24).
“Psychologist Lucy Jo Palladino writes that information overload leads to added stress, indecisiveness,
and less effective analysis of decisions” (Young, p. 24). Case’s Principle of Least Effort (PLE) Theory
explains how the information overload that is present during analysis causes a reduction in accuracy of
analysis. PLE says that an information seeker, like an analyst, will minimize the effort required to obtain
information, even if the result is of lower quality or quantity (Case, p. 291). During Wolfberg’s research
study, he found that analysts that experienced information overload and confusion about the information
being studied would be engaging in survival learning. The analysts would then reduce their analysis of
material and rely on their prior knowledge, this being the analysts least effort available to use in
producing an intelligence product (Wolfberg, p. 12). In research of intelligence processes, it seems that
analysts tend to engage in descriptive analysis of information that is collected, more of the here and now
instead of the future predictions. Davitch attributes this to Daniel Kahneman’s “substitution heuristic” in
which a person will simplify a difficult task by evaluating an easier, related one (Davitch, p. 19). This is
very similar to how Case related the pleasure principle to PLE in information seeking, an analyst will
4. INFORMATION BEHAVIORS IN THE INTELLIGENCE COMMUNITY 4
change the question to get to an answer more quickly, and therefore receiving pleasure at a completed
product (Case, p. 290).
PLE Theory also explains that humans will return to the same source that they have used in the
past, preferably over trying out new sources of information (Case, p. 289). Brueggemann confirms this in
the Illinois State Police Fusion center, explaining that, “Due to time constraints and the number of Daily
Reports, analysts often focus on just one or two from a source (such as Chicago JTTF, Virginia State
Police, Massachusetts State Police, etc.) that is familiar to them based on a prior experience or success
with it (Brueggemann, p.10). Returning to the same sources is something that happens in excess at the
federal level as well. The rise of social media has opened a new opportunity for intelligence professionals
to access large amounts of data, but the intelligence community resists this new information in favor of
the old, classified sources (Davitch, p.18). The unwillingness to look to OPINT sources is a detriment to
the current global threats that face our nation daily.
In looking at the ways that the analysts cycle through the Intelligence Cycle, certain behaviors
seem to remain consistent across the Intelligence Community. One such behavior is the information
literacy that the analysts possess. The LIS community, specifically reference librarians, spends a large
amount of time facilitating the user and information encounter. The IC doesn’t have this same benefit and
there are consequences due to that. Where the reference librarians excel at educating users of ways to
interact with information, the intelligence community is somewhat lacking. “There are few written
guidelines instructing fusion centers as to what is important information and should be forwarded to the
state fusion center; those decisions are left to individual analysts and supervising officers” (Taylor &
Russell, p. 188). Diving deeper, “in fact, the Congressional Research Service reported that the
intelligence cycle has not been fully adopted by state and local agencies. Instead, agencies struggle with
understanding, developing, and implementing a true representation of the fusion process” (Taylor &
Russell, p. 197). What this means is that the intelligence community lacks a clear method for
streamlining their processes of interacting with information, and users are left to figure out their way
amongst several options.
There is an obvious need for more studies and research into applying LIS information behavior
theories to the IC and how the analysts interpret and interact with information of many kinds. Some of
the methods of dealing with information and how to organize it within databases could help make
significant progress in combating the information overload problem that is prevalent in all IC agencies.
Research Methods and Techniques
The Intelligence Community is very difficult to thoroughly study because of the classified nature
of the information that it collects and analyzes. Most of the research used in this report consisted of
surveys and literature reviews. Those researchers that were able to use analysts often had very small
study groups. One research team designed a user study with 3 analysts with varied experience levels.
That research team had analysts’ complete tasks related to analysis and the team collected data through
the analysts written notes, behavior observations, questionnaires and interviews (Gotz, Zhou, & Wen,
2006). Another research team, met with the obstacle of finding analysts, used students attending
Mercyhurst College. “In order to investigate the intelligence analysis process in-depth, we conducted an
observational study of teams of analysts conducting an in-class intelligence project. During the project
period, we conducted two face-to-face meetings with each team – one in week 7 and the other in week 10.
In the meetings, we interviewed each team as a group and the class instructor… (Kang & Stasko, 2014).
5. INFORMATION BEHAVIORS IN THE INTELLIGENCE COMMUNITY 5
Brueggemann (2008) worked with the population and helped to create the very artifact that he wished to
survey and decided to use two research assistants to eliminate bias in the results (Brueggemann, p. 48).
The population of Brueggemann’s survey consisted of 34 criminal intelligence analysts employed by the
Illinois State Police, Illinois National Guard, Federal Bureau of Investigation, Drug Enforcement
Administration, and the Department of Homeland Security (Brueggemann, p. 48). The research assistants
asked the respondents to complete a written survey of 30 closed statements and then seal the results in an
envelope and place the envelope into a box, and the surveys would be collected once all 34 participants
had time to complete the survey (Brueggemann, p. 51).
The Department of Homeland Security also created their own survey of fusion center capabilities,
utilizing a standardized assessment with and scoring methodology. The test was an Online Self-
Assessment Tool that asked multiple choice questions to determine the effectiveness of the fusion centers
according to the employees themselves. Once the survey closed, the DHS employees scoured the results
and compared them with information previously reported and did follow-up phone interviews with fusion
center directors if there were issues with the result matching up (Lincoln & Seegmiller, p. 197).
While this is just a sample of the various ways that the IC was studied, it is obvious that there are
several barriers to completing a thorough survey or research project due to the differences between the
agencies, as well as the classified nature of the material.
Information Sources and Services
The IC uses a variety of sources to obtain information about a subject or target. This type of
intelligence is referred to as all-source intelligence.
One way that all-source intel is shared is through the SIPRNet, which is a classified network that
analysts with secret clearance have access too. The Whitelist is a program on the SIPRNet that contains
classified information, and reports and classified information can be sought about a variety of targets and
subjects (Lincoln & Seegmiller, p. 112). When dealing with international collaboration, the Department
of Defense uses The Department of Defense Intelligence Network (DODIN) in order to make all data
collected available to the intended recipients. This system is secure and allow for many authorized people
to access the classified information in order to perform analyses and make decisions (DOD, p. V-10).
The fusion centers use the Homeland Secure Data Network (HSDN) to connect with federal resources, as
well as the Federal Bureau of Investigation Network (FBINet). The availability of this information is
contained within networks that only certain analysts will have access to based on their clearance levels.
The lack of access for other analysts is one of the issues with reports being doubled, and therefore wasting
valuable analyzing time. High turnover of staff means more access requests and less available analysts to
complete the work needed (Lincoln & Seegmiller, p. 112).
The intelligence cycle is the method that analysts use to gather, analyze, and disseminate
information related to national security issues. According to the Joint Chiefs of Staff, the intelligence
cycle is comprised of planning and direction, collection (which is where the LIS theories overlap),
processing and exploitation, analysis and production, dissemination and integration, and evaluation and
feedback; and these parts will not always be needed in entirety (DOD, p. I-5). Pirolli and Card’s
Sensemaking model for intelligence analysis further accounts for the nature of a nonlinear process during
the intelligence collection process (Kang & Stasko, p. 135). Dervin’s Sense – Making model for user-
centered information gathering is somewhat similar, in that the “situation-gap-use” needs of the user
parallel the needs of the analyst in IC positions (Morris, p. 22). The information needs of different users
may differ regarding context, but the processes and need to fill information gaps remains the same for
both communities.
6. INFORMATION BEHAVIORS IN THE INTELLIGENCE COMMUNITY 6
Related Issues and Considerations
While the focus of this report is the intelligence community tasked with the protection of our
nation’s national security, there are other intelligence fields that could benefit from some LIS strategies.
The business community also uses competitive intelligence to create economic advantages in their niche.
The amount of information there must certainly be as abundant as the amounts found in the IC in this
report. The business intelligence field is a lonely one as well, as most companies don’t want to
collaborate to share intelligence, and the IC is one that needs to work together to succeed to its full
potential.
Some things to consider about the correlation between LIS and the IC is that the government is
very secretive about its information, while the goal of the LIS field is to connect the information to the
user and the user can be anyone who seeks it.
Applications and Implications within the Information Ecology
The reference librarian is someone that possesses many skills related to information seeking. The
IC should look to the LIS community to learn from their experiences with information management and
incorporating user-centered methods into practice. The problem in the IC isn’t a secret. There is too
much information being provided to analysts, without a cohesive and uniform method of organization and
retrieval of intelligence gathered from multiple sources. The disconnect and disorganization creates an
overload of information that prevents analysts from spending more time on the analysis portion of the
intelligence cycle. Several skills of LIS professionals applied to the IC practice would enable more
efficient management and interaction with information in the information ecology. The two disciplines
would benefit from shared knowledge and skills. Showers (2012), describes the process of making data
available for reuse, open and reusable vocabularies and join data together to increase context (Showers, p.
152). The IC has shown struggles with a data-driven infrastructure in the lack of cohesion across the
various local, state, and federal levels. The systems that the FBI use don’t work with the CIA, and the
Treasury Department can’t access any of those materials in some instances. “The lack of an effective
central authority makes those in other agencies reluctant to work with one another” (Taylor & Russell, p.
195). This lack of cohesion is something that deeply affects the timeliness of analysis.
There is also a need for the IC to look at their structure and cooperation between agencies. If all
the agencies have the goal of protecting the United States from enemies that wish us harm, then there
should be more cooperation between them. There have been improvements within the fusion center and
federal entities, but they could be performing much better than they are currently.
Recommendations
The fusion centers and federal agencies need to work together to ensure that the maximum
amount of analysis is being done, which will positively impact the safety of the citizens of the United
States. One way to do this is to ensure a standard training protocol for training and analysis methods, as
well as a way of storing and tagging the analyses. Lincoln and Seegmiller (2013) recommend that
“federal partners should expand support to fusion centers through guidebooks, technical assistance,
mentoring, and subject matter expertise to help fusion centers define and manage SINs (Standing
Information Needs), and to more effectively and efficiently tag their products (Lincoln & Seegmiller, p.
99). By tagging their products, the fusion centers will help to reduce redundant reports that may not have
7. INFORMATION BEHAVIORS IN THE INTELLIGENCE COMMUNITY 7
been found during a search because it was mis-tagged. Federal agencies should also allow access to their
training materials, workshops, and increase their interagency reviews (Lincoln & Seegmiller, p.99).
Another method of improving the information behaviors of the IC is to reframe the education that
is occurring in relation to analysis. Instead of analysts continuing to attend trainings and briefings to learn
to use systems or discuss previously known information, the analysts should be taught how to seek
information, to grow information literacy as a skill for the analyst to rely on to scour through information.
Information literacy at its most basic definition is a person’s ability to acquire and process information to
understand (Frerichs & DiRienzo, p. 71).
Since there are multiple problems with the IC regarding information behaviors, there will most
likely be more than one solution that ends up bringing the IC together to combat the actors that intend to
act against the United States. At the very least, the IC needs to decide on a uniform method and system to
store information that can be accessed across the agency lines. It is a sense of cooperation that is needed,
not the divisive one that persists today.
References
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