This document provides an overview of CSS and WordPress. It discusses selectors, specificity, the box model, floating elements, and common misunderstandings. The summary is:
[1] The document covers CSS fundamentals like selectors, specificity, the box model, and floating elements. It aims to demystify common CSS concepts.
[2] Specificity is explained, with ID selectors having the highest specificity followed by class selectors and element selectors. The last rule defined will override others with equal specificity.
[3] The box model is demonstrated, showing how padding, borders, and margins are added to element widths and heights. Margin collapse is also explained.
This document provides an overview of profiling PHP applications for performance. It begins by discussing common myths about PHP optimizations that provide little real performance benefit. Effective profiling is based on measuring actual performance results using tools. The document outlines different profiling modes for normal development and emergency situations. It then describes various tools that can be used to profile different parts of a PHP application, including the browser, web server, PHP code, database, and operating system. It emphasizes finding and addressing bottlenecks. The document concludes by offering advice like avoiding premature optimization, understanding problems fully before attempting to fix them, and asking others for help.
- Encyclopædia Britannica Online is an online encyclopedia resource for primary, middle, and high school students with over 151,800 encyclopedia articles and 2,100 multimedia elements.
- It has three separate databases tailored for different grade levels to meet the needs of students at different comprehension levels.
- In addition to encyclopedia articles, it also includes resources like a dictionary, thesaurus, current events articles, and teacher materials.
Media Environments and the Dilemma of Collective Action in the Egyptian Revol...Alexander Hanna
The document discusses how new media like social media and regional satellite television helped activists in Egypt overcome the collective action dilemma during the 2011 revolution. It presents a chronology of the revolution and examines how people who got information from different media sources like state TV, Al-Jazeera, and social media varied in their likelihood to participate in protests. The researcher aims to analyze social media data, conduct interviews, and perform content analysis of television to understand how media environments influence collective action.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms for those who already suffer from conditions like depression and anxiety.
The document discusses trends in education technology and digital learning. It notes that teachers are expected to know about various technologies used for communication, learning, and assessments. Peer learning and technology help promote faster learning and the development of young leaders. Blended learning solutions combine different ratios of instructor-led and online learning. The growth of digital content is forcing publishers and booksellers to go digital. Hardware acts as a catalyst for changes in how people access and consume information. Issues around content quality, copyright, and data overload are also mentioned.
This document provides an overview of CSS and WordPress. It discusses selectors, specificity, the box model, floating elements, and common misunderstandings. The summary is:
[1] The document covers CSS fundamentals like selectors, specificity, the box model, and floating elements. It aims to demystify common CSS concepts.
[2] Specificity is explained, with ID selectors having the highest specificity followed by class selectors and element selectors. The last rule defined will override others with equal specificity.
[3] The box model is demonstrated, showing how padding, borders, and margins are added to element widths and heights. Margin collapse is also explained.
This document provides an overview of profiling PHP applications for performance. It begins by discussing common myths about PHP optimizations that provide little real performance benefit. Effective profiling is based on measuring actual performance results using tools. The document outlines different profiling modes for normal development and emergency situations. It then describes various tools that can be used to profile different parts of a PHP application, including the browser, web server, PHP code, database, and operating system. It emphasizes finding and addressing bottlenecks. The document concludes by offering advice like avoiding premature optimization, understanding problems fully before attempting to fix them, and asking others for help.
- Encyclopædia Britannica Online is an online encyclopedia resource for primary, middle, and high school students with over 151,800 encyclopedia articles and 2,100 multimedia elements.
- It has three separate databases tailored for different grade levels to meet the needs of students at different comprehension levels.
- In addition to encyclopedia articles, it also includes resources like a dictionary, thesaurus, current events articles, and teacher materials.
Media Environments and the Dilemma of Collective Action in the Egyptian Revol...Alexander Hanna
The document discusses how new media like social media and regional satellite television helped activists in Egypt overcome the collective action dilemma during the 2011 revolution. It presents a chronology of the revolution and examines how people who got information from different media sources like state TV, Al-Jazeera, and social media varied in their likelihood to participate in protests. The researcher aims to analyze social media data, conduct interviews, and perform content analysis of television to understand how media environments influence collective action.
The document discusses the benefits of exercise for mental health. Regular physical activity can help reduce anxiety and depression and improve mood and cognitive function. Exercise causes chemical changes in the brain that may help protect against mental illness and improve symptoms for those who already suffer from conditions like depression and anxiety.
The document discusses trends in education technology and digital learning. It notes that teachers are expected to know about various technologies used for communication, learning, and assessments. Peer learning and technology help promote faster learning and the development of young leaders. Blended learning solutions combine different ratios of instructor-led and online learning. The growth of digital content is forcing publishers and booksellers to go digital. Hardware acts as a catalyst for changes in how people access and consume information. Issues around content quality, copyright, and data overload are also mentioned.
Objectives:
Setting reactions of Glass-Ionomer Cements (GICs) can be influenced by external factors, such as temperature. The aim of this study was
to test whether thermal treatment of GICs with high power light curing devices improves their mechanical properties.
Methods:
Disc shaped specimens for microhardness (KHN) (3X2.5mm), compressive strength (3X6mm) and diametral tensile strength (6X3mm) tests
were fabricated for: Ketac Molar Aplicap (3M-ESPE), GC Fuji IX (GC), Riva (SDI) and Ionofil® Molar (Voco)(incubated in 100% humidity). The
specimens were divided into 3 subgroups: control and heating for 60 seconds from both sides with either LED – UltraLume 5 (Ultradent)
or QTH - Astralis 10 (Ivoclar) curing lamps (>1000mV/cm²). The mechanical properties were tested (0.5mm/min.): 20 min., 24h, 72h and
one week after mixing. Each combination of material, test, treatment and time included 15 specimens. 3 way and 2 way ANOVA was
conducted for each mechanical test and material respectively.
Results:
Thermal treatment with curing lamps increased surface hardness values (p<0><0.001) for hardness shows that the main influence of the
thermal treatment is evident in the half hour after material mixing (+32.3%), and the influence decreases after 24h, 72h and one week
(+2-2.9%). For compressive strength the influence is +24.8% after half hour and +0.3-7.4% after 24h, 72h and a week.
Conclusions:
Thermal treatment does not change the final mechanical properties of the materials compared to the control (one week), but changes
the kinetics of the setting reaction in a way, that more of the setting occurs in the first half hour.
This document provides guidelines for evaluating and managing neonatal anemia. It discusses the normal physiology of erythropoiesis and defines anemia. The major causes of neonatal anemia are then outlined, including blood loss, increased red blood cell destruction, and decreased red blood cell production. Clinical findings and diagnostic evaluations are reviewed. Management depends on the cause and severity, and may include treating the underlying condition, limiting blood draws, use of erythropoietin, blood transfusions, and partial exchange transfusions for severe cases.
Computer-aided content analysis of digitally enabled movementsAlexander Hanna
The document discusses computer-aided content analysis methods for studying digitally-enabled social movements. It outlines applying supervised machine learning to categorize messages from a Facebook group for Egypt's April 6 Youth Movement. Key points:
1. Categories like offline coordination, online actions, and event reporting are defined to classify a training set of messages.
2. Validation is done using cross-validation, and analysis is applied to the full dataset.
3. Results show peaks in offline coordination before protest dates, but other categories did not change as expected, possibly due to errors in training.
There are many fast data stores, and then there is Redis. Learn about this excellent NoSQL solution that is a powerful in-memory key-value store. Learn how to solve traditionally difficult problems with Redis, and how you can benefit from 100,000 reads/writes a second on commodity hardware. We’ll discuss how and when to use the different datatypes and commands to fit your needs. We’ll discuss the different PHP libraries with their pros and cons. We’ll then show some live examples on how to use it for a chatroom, and how Redis manages a billion data points for our dating matching system. Finally, we’ll discuss some of the upcoming features in the near future, such as clustering and scripting.
Redis is an open source, in-memory data structure store that can be used as a database, cache, or message broker. It supports basic data types like strings, hashes, lists, and sets. Redis features high performance, replication, publishing/subscribing, and Lua scripting. It is widely adopted by companies like GitHub, StackOverflow, and Blizzard for use cases like caching, sessions, queues, and as a real-time database.
For my final year project I used data analysis techniques to investigate user behavior pattern recognition in respect of similar interests and culture versus offline geographical location. This was an out-of-the-box topic, which I selected due to my love on Data Analysis, in respect of the Social Network Analysis in the Internet era.
Pavan Kapanipathi's talk at IBM's Frontiers of Cloud Computing and Big Data Workshop 2014. http://researcher.ibm.com/researcher/view_group_subpage.php?id=5565
Due to the increased adoption of social web, users, specifically Twitter users are facing information overload. Unless a user is willing to restrict the sources (eg number of followings), important information relevant to users' interests often go unnoticed. The reasons include (1) the postings may be at a time the user is not looking for; (2) the user unaware and hence not following the information source; (3) and the information arrives at a rate at which the user cannot consume. Furthermore, some information that are temporally relevant, discovered late might be of no use.
My research addresses these challenges by
(1) Generating user profiles of interests from Twitter using Wikipedia. The interests gleaned from users' Twitter data can be leveraged by personalization and recommendation systems in order to reduce information overload/Volume for users.
(2) Filtering twitter data relevant to dynamically evolving entities. Including Volume, this addresses the velocity challenge in delivering relevant information in real-time. The approach is deployed on Twitris to crawl for dynamic event-relevant tweets for analysis. The prominent aspect of the approaches is the use of crowd-sourced knowledge-base such as Wikipedia.
Ethical Challenges of Using Social Media Data In Research Dr Wasim Ahmed
A talk on the ethical challenges of using social media data in academic research delivered as part of the Bite Size Guide to Research in the 21st Century on the 24th of January, Sheffield, SHARR.
Identifying Influencers on Social Media Using Social Network AnalysisFelipe Bonow Soares
The document discusses using social network analysis to identify influencers on social media. It describes the Social Media Lab and its use of the Netlytic software to analyze social networks and identify influential users. As a case study, the document analyzes Twitter data about Ryerson University to identify different types of influencers in the conversation, concluding that the influential users depend on the metrics and networks examined.
This document summarizes a presentation on analyzing political communication data from Twitter. It discusses analyzing the structure of Twitter data by examining things like retweet networks and interaction patterns, versus analyzing the content of tweets by looking at topics, sentiments, and word frequencies. It provides examples of studies that take both structural and content-based approaches. Specifically, it examines studies that analyzed how Twitter discussions relate to televised political debates and who engages in uncivil language online. The presentation concludes that the most insightful approach is often to combine structural and content-based analyses.
Researching Social Media – Big Data and Social Media AnalysisFarida Vis
Researching Social Media – Big Data and Social Media Analysis, presentation for the Social Media for Researchers: A Sheffield Universities Social Media Symposium, 23 September 2014
Improving the Coverage of Complex Issues with Data Journalism and Digital Met...Liliana Bounegru
This document discusses using digital methods and tools in journalism to improve coverage of complex issues. It provides two examples of how digital mapping was used to analyze topics in UN climate negotiations and connections between counter-jihadist groups on social media. The document also describes several digital tools that can be used for issue mapping, network analysis, and online data collection and analysis. It acknowledges challenges to adopting these methods but also opportunities to help journalists discover new stories and sources and better understand complex networks and relationships.
Twitter analytics: some thoughts on sampling, tools, data, ethics and user re...Farida Vis
Keynote delivered at the SRA Social Media in Social Research conference, London, 24 June, 2013. The presentation highlights some thoughts on sampling, tools, data, ethics and user requirements for Twitter analytics, including an overview of a series of recent tools.
This document discusses cross-platform profiling as a method for studying issues across multiple online spaces. It provides examples of profiling controversies and issues like Fukushima, the economic crisis, hashtags on climate change, and the WCIT conference. Profiling involves analyzing actor composition, key platforms, framing, and variation over time. It demonstrates profiling using tools like the Google scraper and TCAT associational profiler to map word frequencies, co-occurrence networks, and changing associations for issues on Google, Twitter and other platforms. The document raises questions about how media liveliness relates to issue liveliness and how profiling can capture social dynamics and platform specificities.
Objectives:
Setting reactions of Glass-Ionomer Cements (GICs) can be influenced by external factors, such as temperature. The aim of this study was
to test whether thermal treatment of GICs with high power light curing devices improves their mechanical properties.
Methods:
Disc shaped specimens for microhardness (KHN) (3X2.5mm), compressive strength (3X6mm) and diametral tensile strength (6X3mm) tests
were fabricated for: Ketac Molar Aplicap (3M-ESPE), GC Fuji IX (GC), Riva (SDI) and Ionofil® Molar (Voco)(incubated in 100% humidity). The
specimens were divided into 3 subgroups: control and heating for 60 seconds from both sides with either LED – UltraLume 5 (Ultradent)
or QTH - Astralis 10 (Ivoclar) curing lamps (>1000mV/cm²). The mechanical properties were tested (0.5mm/min.): 20 min., 24h, 72h and
one week after mixing. Each combination of material, test, treatment and time included 15 specimens. 3 way and 2 way ANOVA was
conducted for each mechanical test and material respectively.
Results:
Thermal treatment with curing lamps increased surface hardness values (p<0><0.001) for hardness shows that the main influence of the
thermal treatment is evident in the half hour after material mixing (+32.3%), and the influence decreases after 24h, 72h and one week
(+2-2.9%). For compressive strength the influence is +24.8% after half hour and +0.3-7.4% after 24h, 72h and a week.
Conclusions:
Thermal treatment does not change the final mechanical properties of the materials compared to the control (one week), but changes
the kinetics of the setting reaction in a way, that more of the setting occurs in the first half hour.
This document provides guidelines for evaluating and managing neonatal anemia. It discusses the normal physiology of erythropoiesis and defines anemia. The major causes of neonatal anemia are then outlined, including blood loss, increased red blood cell destruction, and decreased red blood cell production. Clinical findings and diagnostic evaluations are reviewed. Management depends on the cause and severity, and may include treating the underlying condition, limiting blood draws, use of erythropoietin, blood transfusions, and partial exchange transfusions for severe cases.
Computer-aided content analysis of digitally enabled movementsAlexander Hanna
The document discusses computer-aided content analysis methods for studying digitally-enabled social movements. It outlines applying supervised machine learning to categorize messages from a Facebook group for Egypt's April 6 Youth Movement. Key points:
1. Categories like offline coordination, online actions, and event reporting are defined to classify a training set of messages.
2. Validation is done using cross-validation, and analysis is applied to the full dataset.
3. Results show peaks in offline coordination before protest dates, but other categories did not change as expected, possibly due to errors in training.
There are many fast data stores, and then there is Redis. Learn about this excellent NoSQL solution that is a powerful in-memory key-value store. Learn how to solve traditionally difficult problems with Redis, and how you can benefit from 100,000 reads/writes a second on commodity hardware. We’ll discuss how and when to use the different datatypes and commands to fit your needs. We’ll discuss the different PHP libraries with their pros and cons. We’ll then show some live examples on how to use it for a chatroom, and how Redis manages a billion data points for our dating matching system. Finally, we’ll discuss some of the upcoming features in the near future, such as clustering and scripting.
Redis is an open source, in-memory data structure store that can be used as a database, cache, or message broker. It supports basic data types like strings, hashes, lists, and sets. Redis features high performance, replication, publishing/subscribing, and Lua scripting. It is widely adopted by companies like GitHub, StackOverflow, and Blizzard for use cases like caching, sessions, queues, and as a real-time database.
For my final year project I used data analysis techniques to investigate user behavior pattern recognition in respect of similar interests and culture versus offline geographical location. This was an out-of-the-box topic, which I selected due to my love on Data Analysis, in respect of the Social Network Analysis in the Internet era.
Pavan Kapanipathi's talk at IBM's Frontiers of Cloud Computing and Big Data Workshop 2014. http://researcher.ibm.com/researcher/view_group_subpage.php?id=5565
Due to the increased adoption of social web, users, specifically Twitter users are facing information overload. Unless a user is willing to restrict the sources (eg number of followings), important information relevant to users' interests often go unnoticed. The reasons include (1) the postings may be at a time the user is not looking for; (2) the user unaware and hence not following the information source; (3) and the information arrives at a rate at which the user cannot consume. Furthermore, some information that are temporally relevant, discovered late might be of no use.
My research addresses these challenges by
(1) Generating user profiles of interests from Twitter using Wikipedia. The interests gleaned from users' Twitter data can be leveraged by personalization and recommendation systems in order to reduce information overload/Volume for users.
(2) Filtering twitter data relevant to dynamically evolving entities. Including Volume, this addresses the velocity challenge in delivering relevant information in real-time. The approach is deployed on Twitris to crawl for dynamic event-relevant tweets for analysis. The prominent aspect of the approaches is the use of crowd-sourced knowledge-base such as Wikipedia.
Ethical Challenges of Using Social Media Data In Research Dr Wasim Ahmed
A talk on the ethical challenges of using social media data in academic research delivered as part of the Bite Size Guide to Research in the 21st Century on the 24th of January, Sheffield, SHARR.
Identifying Influencers on Social Media Using Social Network AnalysisFelipe Bonow Soares
The document discusses using social network analysis to identify influencers on social media. It describes the Social Media Lab and its use of the Netlytic software to analyze social networks and identify influential users. As a case study, the document analyzes Twitter data about Ryerson University to identify different types of influencers in the conversation, concluding that the influential users depend on the metrics and networks examined.
This document summarizes a presentation on analyzing political communication data from Twitter. It discusses analyzing the structure of Twitter data by examining things like retweet networks and interaction patterns, versus analyzing the content of tweets by looking at topics, sentiments, and word frequencies. It provides examples of studies that take both structural and content-based approaches. Specifically, it examines studies that analyzed how Twitter discussions relate to televised political debates and who engages in uncivil language online. The presentation concludes that the most insightful approach is often to combine structural and content-based analyses.
Researching Social Media – Big Data and Social Media AnalysisFarida Vis
Researching Social Media – Big Data and Social Media Analysis, presentation for the Social Media for Researchers: A Sheffield Universities Social Media Symposium, 23 September 2014
Improving the Coverage of Complex Issues with Data Journalism and Digital Met...Liliana Bounegru
This document discusses using digital methods and tools in journalism to improve coverage of complex issues. It provides two examples of how digital mapping was used to analyze topics in UN climate negotiations and connections between counter-jihadist groups on social media. The document also describes several digital tools that can be used for issue mapping, network analysis, and online data collection and analysis. It acknowledges challenges to adopting these methods but also opportunities to help journalists discover new stories and sources and better understand complex networks and relationships.
Twitter analytics: some thoughts on sampling, tools, data, ethics and user re...Farida Vis
Keynote delivered at the SRA Social Media in Social Research conference, London, 24 June, 2013. The presentation highlights some thoughts on sampling, tools, data, ethics and user requirements for Twitter analytics, including an overview of a series of recent tools.
This document discusses cross-platform profiling as a method for studying issues across multiple online spaces. It provides examples of profiling controversies and issues like Fukushima, the economic crisis, hashtags on climate change, and the WCIT conference. Profiling involves analyzing actor composition, key platforms, framing, and variation over time. It demonstrates profiling using tools like the Google scraper and TCAT associational profiler to map word frequencies, co-occurrence networks, and changing associations for issues on Google, Twitter and other platforms. The document raises questions about how media liveliness relates to issue liveliness and how profiling can capture social dynamics and platform specificities.
A 1015 update to the 2012 "Data Big and Broad" talk - http://www.slideshare.net/jahendler/data-big-and-broad-oxford-2012 - extends coverage, brings more in context of recent "big data" work.
The document describes a proposed approach for inferring implicit topical interests of users on Twitter. It discusses related work on detecting user interests from social media using bag-of-words, topic modeling, and bag-of-concepts approaches. The proposed approach models user interests as a graph-based link prediction problem over a heterogeneous graph incorporating user followerships, explicit interests, and topic relatedness. It evaluates different variants of the model and finds semantic relatedness of topics to be most effective for identifying implicit user interests.
1. Sentiment analysis involves using natural language processing, statistics, or machine learning to identify and extract subjective information like opinions, attitudes, and emotions from text.
2. It can analyze sentiment at different levels of granularity, such as document, sentence, or entity level.
3. Sentiment analysis has many applications including understanding customer opinions, predicting election results, and improving marketing strategies.
4. Performing accurate sentiment analysis requires understanding the concept of an opinion as a quintuple that identifies the target, aspect, sentiment polarity, opinion holder, and time.
Analyzing User Modeling on Twitter for Personalized News RecommendationsGUANGYUAN PIAO
Presentation for reading group 30/09/2015, Check out my recent work http://parklize.github.io/#research on User Modeling which is motivated by this presentation.
Using Twitter as a data source: An overview of ethical challengesDr Wasim Ahmed
Slides from a conference presentation on the ethical challenges of using Twitter as a data source presented at the Ethics and Social Media Research Conference.
Organsied by the Research Ethics Group of the Academy of Social Sciences and the NSMNSS network the one-day conference aimed to further develop and explore the ethics of social science research using social media.
This document summarizes Anatoliy Gruzd's presentation on research with social media data and considerations around data stewardship and ethics. It discusses key aspects of working with social big data including collection from APIs and data resellers, analysis through visualization, network and geo-based analysis, and preservation efforts from public archives, private companies and personal archiving. It also covers ethical considerations for researchers, industry and users around topics like transparency, privacy and expectations of data use. The presentation emphasizes the importance of responsible data stewardship across the whole data lifecycle from collection to analysis to preservation.
Mapping Movements: Social movement research and big data: critiques and alter...Tim Highfield
Paper presented by Sky Croeser and Tim Highfield at Compromised Data? colloquium, Toronto, Canada, 29 October 2013. http://www.infoscapelab.ca/news/oct-28-29-colloquium-compromised-data-new-paradigms-social-media-theory-and-methods
[Tim's additional note: This presentation is focused specifically on doing research around social movements and producing findings and contributing new knowledge about how activists use social media and online technologies – there is some very important and detailed quantitative analysis of Twitter discussions around social movements and uprisings which provide critical information about communication online and responses to international events, and my intent is not to discount this work just because it is quant-only – these studies do different things and have different aims, and so the scope of their findings is not the same by extension (I’m not sure that I made this point clearly in the presentation, though).]
Working with Social Media Data: Ethics & good practice around collecting, usi...Nicola Osborne
Slides from a workshop delivered for the University of Edinburgh Digital Scholarship programme, on 18th October 2017. For further information on the programme see: http://www.digital.cahss.ed.ac.uk/ or #DigScholEd. If you are interested in hosting a similar workshop, or adapting these slides please contact me: nicola.osborne@ed.ac.uk.
Data augmented ethnography: using big data and ethnography to explore candi...Salla-Maaria Laaksonen
In this paper we propose data augmented ethnography as a novel mixed methods approach to combine ethnographic, qualitative, observations with social media data collection and computational analysis. Using two brief studies on online interaction as examples we discuss the benefits and challenges of the combination of these two perspectives. We posit that the observations made in the qualitative phase can be quantified and hypothesized together with the data collected later during the analysis stage. Through our case studies we aim to shed light to the differences apparent on the party level and seek to understand how candidates, based on their parties political standing, differ in terms of interactivity. We ask, what insights does a mixed-method approach combining ethnographic observations to computational social science offer to the study of interactivity and its many pregnant forms? To answer this question, we use a large data set collected from different social media platforms before and during the 2015 Parliament Election in Finland. This data consists of both textual data including all candidate updates and the conversations they elicited, as well as field notes written and collected during ethnographic field work period before the elections.
Similar to Large scale Twitter collection of 2012 US election (20)
Data augmented ethnography: using big data and ethnography to explore candi...
Large scale Twitter collection of 2012 US election
1. 2012 Twitter
collection
Alexander
Hanna
Research
Agenda
Current
Large scale Twitter collection of 2012 US
Project
Case Study
election
Future
Approaches
Alexander Hanna
Department of Sociology
University of Wisconsin-Madison
ahanna@ssc.wisc.edu
@alexhanna
September 14, 2012
2. 2012 Twitter
collection
Alexander A Twitter-specific Research
Hanna
Agenda
Research
Agenda
Current
Project
Case Study
Future
Approaches
• How different is the political Twitterverse from the rest
of the social graph?
• What are the different modes of engagement between
different types of elite users and their followers?
• How does information flow from elite users to others?
3. 2012 Twitter
collection
Alexander A Twitter-specific Research
Hanna
Agenda
Research
Agenda
Current
Project
Case Study
Future
Approaches
• How different is the political Twitterverse from the rest
of the social graph?
• What are the different modes of engagement between
different types of elite users and their followers?
• How does information flow from elite users to others?
4. 2012 Twitter
collection
Alexander A Twitter-specific Research
Hanna
Agenda
Research
Agenda
Current
Project
Case Study
Future
Approaches
• How different is the political Twitterverse from the rest
of the social graph?
• What are the different modes of engagement between
different types of elite users and their followers?
• How does information flow from elite users to others?
5. 2012 Twitter
collection
Alexander Current Study
Hanna
Research
Agenda
Current
Project
Case Study
Future
Approaches
• Structured to consider direct follow relationships
• Constructing the political Twitterverse
6. 2012 Twitter
collection
Alexander Political elites
Hanna
Research
Agenda
Current
Project
Case Study
• Candidates in national races
Future
Approaches • Party leadership
• Media - Pundits, Reporters, Bloggers
• Satirists
• Celebrities
• Advocacy Groups
7. 2012 Twitter
collection
Alexander Sampling Strategy
Hanna
Research
Agenda Three levels - Elites and followers
Current
Project
Case Study
Future
Approaches
8. 2012 Twitter
collection
Alexander Waves of collection
Hanna
Research
Agenda
Current
Project
Case Study
Future
Approaches
Sampling at three different points
• Pre-primary - Mid January
• Post-primary - June 26
• Post-convention and pre-election - September 7
9. 2012 Twitter
collection
Alexander Data Collection and Processing
Hanna
Research
Agenda
Current
Project
Case Study
Future • Twitter RESTful API for collecting follower lists
Approaches
• Twitter Streaming API for collecting tweets
• Two streams - targeted sample stream and
“gardenhose” (10% sample of all of Twitter)
• Hadoop/MapReduce for analysis
10. 2012 Twitter
collection
Alexander Data size and storage
Hanna
Research
Agenda
Current
Project
Case Study
• Gardenhose
Future • 2.7 TB
Approaches • 20-40mil tweets/day
• 15-16 GB/day
• Targeted sample:
• 77,054 unique users
• 103 GB
• 500k-1mil tweets/day
• Currently around 1 GB/day
11. 2012 Twitter
collection
Alexander Case Study in Agenda Setting
Hanna
Research
Agenda
Current
Project
Case Study
Future
Approaches
Who establishes the media discourse? How do different
elements of media try to set the discourse?
12. 2012 Twitter
collection
Alexander Trayvon Martin
Hanna
Research
Agenda • February 26 - Martin
Current
Project
killed
Case Study • March 8 - CBS News
Future
Approaches
interview with Martin’s
parents
• Week of March 12 -
Media catches on, case
more covered than
presidential race
• April 11 - State
Prosecuter files charges
• April 19 - Zimmerman
released on bond
13. 2012 Twitter
collection
Alexander Twitter mentions
Hanna
Research
Agenda 1.0
Current
Project
Case Study 0.8
Future
Approaches
0.6
factor(Keyword)
Count
trayvon
zimmerman
0.4
0.2
03/01 03/05 03/09 03/13 03/17 03/21 03/25 03/29 04/02 04/06 04/10 04/14 04/18 04/22 04/26 04/30 05/04
Date
14. 2012 Twitter
collection
Alexander Twitter vs. Google
Hanna
Research
Agenda 1.0
Current
Project
Case Study 0.8
Future
Approaches
0.6
factor(Keyword)
trayvon
Count
zimmerman
Gzimmerman
Gtrayvon
0.4
0.2
0.0
03/01 03/05 03/09 03/13 03/17 03/21 03/25 03/29 04/02 04/06 04/10 04/14 04/18 04/22 04/26 04/30 05/04
Date
15. 2012 Twitter
collection
Alexander Setting the agenda
Hanna
Mentions of Trayvon
Research
Agenda
Current
Project
Case Study 0.05
Future
Approaches
0.04
factor(Level)
0.03 1
Ratio
2
3
0.02
0.01
03/01 03/05 03/09 03/13 03/17 03/21 03/25 03/29 04/02 04/06 04/10 04/14 04/18 04/22 04/26 04/30 05/04
Date
16. 2012 Twitter
collection
Alexander Setting the agenda
Hanna
Mentions of Zimmerman
Research
Agenda
Current
Project
0.030
Case Study
Future
Approaches 0.025
0.020
factor(Level)
1
Ratio
2
3
0.015
0.010
0.005
03/01 03/05 03/09 03/13 03/17 03/21 03/25 03/29 04/02 04/06 04/10 04/14 04/18 04/22 04/26 04/30 05/04
Date
17. 2012 Twitter
collection
Alexander Setting the agenda
Hanna
Research
Agenda
Current
Project
Case Study
• No noticable difference
Future
Approaches between mentions of
Trayvon in elites vs.
followers
• However, followers seem
to catch on to
Zimmerman quicker
18. 2012 Twitter
collection
Alexander Future Work
Hanna
Research
Agenda
Current
Project
Case Study
Future • Incorporating network structure
Approaches
• Follower/friend networks
• User mention networks
• Retweet patterns
• Computer-aided content analysis
• Machine learning (supervised and unsupervised)
19. 2012 Twitter
collection
Alexander Future Work
Hanna
Research
Agenda
Current
Project
Case Study
Future
Approaches
Thanks!
ahanna@ssc.wisc.edu
@alexhanna