The document describes a team called Narrative Mind that seeks to develop tools to optimize discovery and investigation of communication trends on social media. It provides details on the team's experts, interviews conducted, resources and partnerships. Potential key activities and timelines are outlined. Value propositions and customer jobs/pains are described for potential government and commercial customers, including helping prioritize issues, improving planning and decision making, and monitoring brands and identifying emerging issues.
The Narrative Mind team seeks to develop tools to optimize discovery and investigation of communication trends on social media for the US Army Cyber Command (ARCYBER). They have conducted 46 interviews with users, experts, and buyers. Their focus has evolved to identifying narratives in real time based on updated guidance from ARCYBER. They plan to further define what a "narrative" means, research how companies visualize narratives, and expand their network of beneficiaries.
The Narrative Mind team seeks to develop tools to optimize discovery and investigation of communication trends on social media. They have conducted 66 interviews total with experts, users, and potential buyers. The team hypothesizes that their narrative detection units may overlap with other commercial tools, and plan to do a demo day to compare capabilities. They have proposed an MVP approach of outputting 3 types of narratives to analysts based on frequency of units associated with real-world narratives.
The document describes a team called Narrative Mind that seeks to develop tools to optimize discovery and investigation of communication trends on social media. It provides details on the team's experts, interviews conducted, resources and partnerships. Potential key activities and timelines are outlined. Value propositions and customer jobs/pains are described for potential government and commercial customers, including helping prioritize issues, improving planning and decision making, and monitoring brands and identifying emerging issues.
The Narrative Mind team seeks to develop tools to optimize discovery and investigation of communication trends on social media for the US Army Cyber Command (ARCYBER). They have conducted 46 interviews with users, experts, and buyers. Their focus has evolved to identifying narratives in real time based on updated guidance from ARCYBER. They plan to further define what a "narrative" means, research how companies visualize narratives, and expand their network of beneficiaries.
The Narrative Mind team seeks to develop tools to optimize discovery and investigation of communication trends on social media. They have conducted 66 interviews total with experts, users, and potential buyers. The team hypothesizes that their narrative detection units may overlap with other commercial tools, and plan to do a demo day to compare capabilities. They have proposed an MVP approach of outputting 3 types of narratives to analysts based on frequency of units associated with real-world narratives.
The document summarizes an aquaLink project that aims to create a wearable device for monitoring the health and safety of U.S. Navy divers. The device would record critical data like vitals and make it actionable through real-time alerts and post-dive analytics. A team of four is working on the project, with expertise in hardware engineering, mechatronics, international policy, and product design. The project is sponsored by the U.S. Navy Special Warfare Group 3 and aims to protect both the short- and long-term health of divers through collecting and analyzing dive data.
Team Guardian is developing countermeasures against commercial drones for the U.S. Army Asymmetric Warfare Group, with their initial focus being on prototyping an automatic threat detection and classification system to identify the type of drone and potential threats it poses at demonstrations. They have conducted customer discovery interviews with stakeholders from military installations and are refining their minimum viable product based on feedback to provide scalable and easy-to-use counter-drone capabilities.
Skynet is developing autonomous drones for situational awareness to help prevent battlefield fatalities. They have interviewed 43 people total including 10 this week, consisting of 4 users, 3 buyers, and 3 experts. Their minimum viable product will integrate drone footage with image recognition into the ATAK interface to identify and track friendlies and detect objects and threats. Key activities include demonstrations to gain support, showing opportunities to fill capability gaps cost effectively. Risks include misclassifications leading to injury and competition from other programs.
Capella Space provides low-cost SAR imagery from a satellite constellation with a high revisit rate. The company has interviewed image resellers and customers in industries like maritime awareness and oil and gas. Capella is developing payloads, algorithms, and satellites to deploy 1-3 satellites by September 2017 and a full 40 satellite constellation by 2020 to provide global coverage and on-demand imagery.
The document summarizes an aquaLink project that aims to create a wearable device for monitoring the health and safety of U.S. Navy divers. The device would record critical data like vitals and make it actionable through real-time alerts and post-dive analytics. A team of four is working on the project, with expertise in hardware engineering, mechatronics, international policy, and product design. The project is sponsored by the U.S. Navy Special Warfare Group 3 and aims to protect both the short- and long-term health of divers through collecting and analyzing dive data.
Team Guardian is developing countermeasures against commercial drones for the U.S. Army Asymmetric Warfare Group, with their initial focus being on prototyping an automatic threat detection and classification system to identify the type of drone and potential threats it poses at demonstrations. They have conducted customer discovery interviews with stakeholders from military installations and are refining their minimum viable product based on feedback to provide scalable and easy-to-use counter-drone capabilities.
Skynet is developing autonomous drones for situational awareness to help prevent battlefield fatalities. They have interviewed 43 people total including 10 this week, consisting of 4 users, 3 buyers, and 3 experts. Their minimum viable product will integrate drone footage with image recognition into the ATAK interface to identify and track friendlies and detect objects and threats. Key activities include demonstrations to gain support, showing opportunities to fill capability gaps cost effectively. Risks include misclassifications leading to injury and competition from other programs.
Capella Space provides low-cost SAR imagery from a satellite constellation with a high revisit rate. The company has interviewed image resellers and customers in industries like maritime awareness and oil and gas. Capella is developing payloads, algorithms, and satellites to deploy 1-3 satellites by September 2017 and a full 40 satellite constellation by 2020 to provide global coverage and on-demand imagery.
This document provides information on activities, resources, and partners from the previous week of an advanced lecture series. It also prepares for budgeting needs for the upcoming week's mission. Specifically, it discusses:
1) Takeaways from the previous week's discussion on activities, resources, and partners.
2) Examples of mission budgets needed to fund planned activities, including timing of required funds.
3) An example mission case study on developing renewable energy solutions to reduce fuel reliance for deployed military units. Details on the mission model, budget needs, and timeline are given.
The document describes AquaLink, a proposed system to improve situational awareness for Navy divers. AquaLink would use buoys with GPS and satellite communication capabilities to provide divers and their support teams with location information and a communication channel to aid mission success. The document discusses initial prototypes, including a buoy with GPS and Iridium satellite communication that could be easily deployed and retrieved by divers.
Lecture 7 Activities, Resources and Partners H4D Stanford 2016Stanford University
This document provides an example of an energy initiative called Energy to the Edge (E2E) that aims to equip deployed military units with renewable energy solutions to reduce reliance on fuel resupply. It outlines the initiative's key activities, resources, partners, beneficiaries and budget. Some key points:
- The initiative focuses on providing energy to remote outposts where fuel resupply is most expensive.
- It identifies various military partners needed to support the initiative and requirements like testing, funding, training and installation.
- Resources required include engineering support, testing contracts, transportation and funding for initial deployment sets and testing.
- The goal is to reduce fuel consumption, deployment costs, and supply convoys
Capella Space aims to provide global satellite imagery to customers. After interviewing potential beneficiaries, Capella realized it needed to pivot its approach. It will now focus on deploying a small number of satellites in equatorial orbit to address problems like illegal fishing for countries in that region, rather than aiming for a large global satellite constellation. This will allow it to meet customer needs with fewer satellites and a focus on actionable processed imagery rather than raw data.
The document describes the progress of a team working with the US Army Cyber Command (ARCYBER) to develop tools for analyzing adversary communication trends on social media. After initial interviews to understand the problem, the team mapped out the problem space and identified opportunities. They proposed exploring co-occurrence of hashtags as a potential minimum viable product. To prove this prototype, the team gathered a dataset of 600k tweets coded 1300 hashtag sets. They are working to demonstrate this prototype meets ARCYBER's needs and could be integrated into their workflow. The next steps involve applying to work with ARCYBER through the Other Transaction Authority process to continue iterative testing and development.
Avoiding Anonymous Users in Multiple Social Media Networks (SMN)paperpublications3
Abstract: The main aim of this project is secure the user login and data sharing among the social networks like Gmail, Facebook and also find anonymous user using this networks. If the original user not available in the networks, but their friends or anonymous user knows their login details means possible to misuse their chats. In this project we have to overcome the anonymous user using the network without original user knowledge. Unauthorized user using the login to chat, share images or videos etc This is the problem to be overcome in this project .That means user first register their details with one secured question and answer. Because the anonymous user can delete their chat or data In this by using the secured questions we have to recover the unauthorized user chat history or sharing details with their IP address or MAC address. So in this project they have found out a way to prevent the anonymous users misuse the original user login details.
This document discusses a proposed system for segmenting tweets and applying that segmentation to name entity recognition. The proposed system uses k-means clustering to segment tweets into categories like Bollywood, business, education, politics, and sports. This segmentation aims to preserve the semantic meaning of tweets and improve downstream applications like named entity recognition, achieving better accuracy than word-based approaches. The proposed system also adds security features like blocking users and is intended to be more efficient and flexible than prior algorithms.
IRJET- Big Data Driven Information Diffusion Analytics and Control on Social ...IRJET Journal
This document discusses controlling the spread of fake or misleading information on social media. It proposes a system to analyze information diffusion on social networks, identify diffused data, and control the spread of fake diffused data. The system would extract data from social media, perform sentiment analysis to determine the veracity of information, and discard fake or untrustworthy information from the database to prevent further propagation. A variety of machine learning techniques could be used for the sentiment analysis, including naive Bayes classification, linear regression, and gradient boosted trees. The goal is to curb the spread of misinformation while still allowing the diffusion of real or truthful information.
This document discusses different approaches for analyzing social media data to gain customer insights:
1) Channel reporting tools provide overviews of specific social media platforms but lack deeper insights.
2) Scorecard systems aggregate data across sources but users cannot enhance the data.
3) Text mining analyzes sentiment but network analysis examines relationships; each technique has limitations alone.
4) The document proposes combining text mining, network analysis, and other techniques using a predictive analytics platform to generate new insights, as was done successfully for a major European telecom company.
It provides examples analyzing publicly available Slashdot data to identify influencers and show how sentiment relates to influence.
ML&AI APPROACH TO USER UNDERSTANDING ECOSYSTEM AT VCCORP Applications to News...Tuan Hoang
Introduce the ML&AI approach to user understanding at VCCORP with many applications, including news distribution, recommendation engine in news, e-commerce, and the advertising technology
The document presents a proposed approach for sentiment analysis on big social data using Spark. It discusses collecting opinions from social media to analyze large events by tracking public behavior in real-time. The proposed system provides a adaptable sentiment analysis approach using Spark that analyzes social media posts and classifies them by subject in real-time. It also discusses using sentiment data from social media to inform decisions.
This document summarizes a study analyzing social media influence and credibility. A team of students and professors extracted different types of data from Twitter, including mentions of users, tweets by authorities, and keywords. They developed a semantic parser to analyze tweet content using ontological semantic technology. An initial linear score was formulated to measure user influence, and network analysis identified pivotal users between communities. Validation will compare content analysis to real-world events to supplement credibility assessment. The study has potential applications in public policy, business, psychology, and traffic monitoring.
23 may 2015 monitoring & analyzing social media Mats Björe
Our approach to social media analytics focuses on analyzing social media data to better understand interactions and influence. We aim to identify, monitor, track, and measure influence and reach to build dynamic dossiers and provide decision support. Some key challenges include fragmented information lacking context, use of symbols and emoticons, similar messages from many sources, and constantly changing platforms and user preferences. We use proven software like Silobreaker to monitor social media at scale and provide analytical dashboards and tools to examine specific stakeholders, anomalies, timelines, exposure, locations, and networks.
Obama's 2012 reelection campaign leveraged big data analytics to build detailed profiles of potential voters using disparate data sources. They combined this data to create a "single view" of individuals to optimize fundraising, volunteer mobilization, and get-out-the-vote strategies. Predictive modeling was used to score voters by likelihood of donating or voting Democrat. Resources were targeted to persuadable voters in swing states. Regular polling provided insights to track debate impacts and allocate campaign efforts. The campaign's data-driven approach helped achieve record fundraising and turnout in swing states.
A network based model for predicting a hashtag break out in twitter Sultan Alzahrani
Online information propagates differently on the web, some
of which can be viral. In this paper, first we introduce a simple standard deviation sigma levels based Tweet volume breakout definition, then we proceed to determine patterns of re-tweet network measures to predict whether a hashtag volume will breakout or not. We also developed a visualization tool to help trace the evolution of hashtag volumes, their underlying networks and both local and global network measures. We trained a random forest tree classifier to identify effective network measures for predicting hashtag volume breakouts. Our experiments showed that “local” network features, based on a fixed-sized sliding window, have an overall predictive accuracy of 76 %, where as, when we incorporate “global” features that utilize all interactions up to the current period, then the overall predictive accuracy of a sliding window based breakout predictor jumps to 83 %.
Diy research trends webinar(2) revised(2)QuestionPro
The document summarizes top marketing research trends, including using social media and text analytics to track consumer sentiment, running surveys on mobile devices, and crowdsourcing ideas from customers. It also promotes several tools from Survey Analytics and partner companies that can help companies take advantage of these trends, such as DiscoverText for text analysis, IdeaScale for crowdsourcing, and SurveySwipe/SurveyPocket for mobile surveys.
This document discusses the social media analysis solution space. It describes who the solution providers are (researchers, software, services), what they provide (social media analysis and analytics-infused advisory services), who they serve (business users), and how (through various technologies). The document also outlines some key business questions that social media analysis can help answer, and the different approaches taken by industry to work backwards from goals and insights to determine appropriate data, methods, and presentations.
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
Brand Analytics is a social media monitoring and analytics platform that tracks brand references across social media and online media. It provides automatic sentiment analysis of messages, determines important topics and trends, and visualizes data through intuitive reports and charts. The system collects a comprehensive set of messages about monitored objects from various social networks and data sources. It performs linguistic analysis including sentiment detection and geotagging of messages. Reports can be filtered, exported, and accessed through the cloud-based SaaS model or integrated on-site. The platform is used to support marketing, PR, strategy, and customer service functions.
Óscar Méndez - Big data: de la investigación científica a la gestión empresarialFundación Ramón Areces
El 3 de julio de 2014, organizamos en la Fundación Ramón Areces una jornada con el lema 'Big Data: de la investigación científica a la gestión empresarial'. En ella estudiamos los retos y oportunidades del Big data en las ciencias sociales, en la economía y en la gestión empresarial. Entre otros ponentes, acudieron expertos de la London School of Economics, BBVA, Deloite, Universidades de Valencia y Oviedo, el Centro Nacional de Supercomputación...
Agile Data Science is a lean methodology that is adopted from Agile Software Development. At the core it centers around people, interactions, and building minimally viable products to ship fast and often to solicit customer feedback. In this presentation, I describe how this work was done in the past with examples. Get started today with our help by visiting http://www.alpinenow.com
Sentiment Analysis is the process of finding the sentiments from different classes of words.
Generally speaking, sentiment analysis aims to determine the attitude of a speaker or a writer with
respect to some topic or the overall contextual polarity of a document. The attitude may be his or
her judgment or evaluation, affective state, or the intended emotional communication. In this case,
‘tweets’! Given a micro-blogging platform where official, verified tweets are available to us, we
need to identify the sentiments of those tweets. A model must be constructed where the sentiments
are scored, for each product individually and then they are compared with, diagrammatically,
portraying users’ feedback from the producers stand point.
There are many websites that offer a comparison between various products or services based on
certain features of the article such as its predominant traits, price, and its welcome in the market and
so on. However not many provide a juxtaposing of commodities with user review as the focal point.
Those few that do work with Naïve Bayes Machine Learning Algorithms, that poses a disadvantage
as it mandatorily assumes that the features, in our project, words, are independent of each other.
This is a comparatively inefficient method of performing Sentiment Analysis on bulk text, for
official purposes, since sentences will not give the meaning they are supposed to convey, if each
word is considered a separate entity. Maximum Entropy Classifier overcomes this draw back by
limiting the assumptions it makes of the input data feed, which is what we use in the proposed
system.
This document discusses social data mining. It begins by defining data, information, and knowledge. It then defines data mining as extracting useful unknown information from large datasets. Social data mining is defined as systematically analyzing valuable information from social media, which is vast, noisy, distributed, unstructured, and dynamic. Common social media platforms are described. Graph mining and text mining are discussed as important techniques for social data mining. The generic social data mining process of data collection, modeling, and various mining methods is outlined. OAuth 2.0 authorization is also summarized as an important process for applications to access each other's data.
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The document describes a team's efforts to commercialize a new protein quantification technology called PLA-Seq. After initially thinking the technology's value propositions of lower cost, faster throughput, and lower sample volume would appeal to pharmaceutical and personalized health companies, the team conducted customer interviews and learned accuracy was more important than cost to most customers. They also found their target markets should be preclinical biotech and academia rather than personalized health or CROs. The team incorporated their business and pivoted their marketing strategy and funding plans accordingly based on learnings outside of the building.
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2. Team Info
Sponsor: US Army Cyber Command (ARCYBER)
The Narrative Mind team contains experts in software engineering, social media design, and
web-based information operations (IO). We seek to develop tools that will optimize discovery
and investigation of communication trends on social media.
Weekly Total: 10 interviews
Users: 14
Experts: 38
Buyers: 4
Cumulative Total: 56 interviews
3. Problem
Statements,
NOT RFPs
Creates
“Innovation
Challenges”
Organizational Chart
CW3 “Fitzgerald”
MAJ “Kramer”
Reports analysis
COL “Tim”
LTC “Zeke”
Director & Deputy SIG
Assesses threats 1-
3yrs out
Proposes
CONOPs
BG Frost
Deputy
Commander Ops
ARCYBER
(Service Component)
NSA
ADM Rogers
Internal ARCYBER office
Program Managers
LTG Cardon
Commanding General
BG (O8-level)
Undergoing Leadership
Change
Contains own cyber
troops that carry out cyber
missions.
JOINT FORCES HQ-CYBER
USCYBERCOM
ADM Rogers
USSTRATCOM
COCOMs
CENTCOM,
AFRICOM,
NORTHCOM
Proposes
concepts
Secretary Carter
ARCYBER
Acquisition
Process
Mr. R. Pontius
Deputy to Commanding
General, Civilian
COL “John”
G3 Operations
Subordinate
Units:
- 1st IO Cmnd.
- 780th Military
Intelligence
Brigade
- NETCOM
Fully-staffed Joint
Force IO/SIGINT
troops.
Provides
specialized
analysis on ad
hoc basis.
Proposes
concepts
to be
implemented
C5 Consortium
President Charlie McBride
Board of Directors
Companies/Academics (by application)
Traditional DoD
Contractors
Non-traditional
Contractors
DIUX
Develops relationships
with commercial sector.
Submit White Papers
& Demos
Necessary
Partnership
Started 2015
PEO-EIS
ACT
Advanced
Concepts and
Technology
Directorate
Manages
CYBER
capabilities/
requirements.
4. Other Transactional Authorities
Key Objectives of OTAs:
● Reduce barriers to entry.
● Incentivize commercial
participation through expedited
awards and negotiable IP
terms.
Necessary Conditions of OTAs:
● Prototype projects only.
● Enhances mission effectiveness.
● Costs are fair/reasonable.
At least one criterion must be met:
● All significant participants are
small businesses or non-traditional
defense contractors.
● Non-traditional defense contractor
participates to a significant extent.
● One-third cost share for traditional
defense contractor
Example of Actual Cyber OTA Micro Cloud Computing System
OTA Timeline
5. All the Hypotheses
Global
Tweet-level
Awareness Response
Adversary IO Org Chart
No baseline for monitoring/aggregating
adversary use of tech; cyber targeting
Automatic Narrative Detection
Language/culture experts aren’t able
to work at scale
Virality Predictor
Understand which narratives are the most salient
Important Event Predictor
Preempt real world events
Counter-Narrative Generator
DoD/Gvt. social media
presence is weak
Persistent ID-Alias tracker
Account bans and multiple aliases across
different networks make IDs hard to track
Poison Link Generator
Monitor who views
adversary dark-web
content
Filesharing Site Scraper
Need more cached information
access
Expedited Content Categorization
Scale of social media makes manual efforts
painful
Bot Detector
Can’t determine actual scale of
adversary following and support.
6. Hypotheses ❏ Three previously proposed narrative units would be valuable to track.
- Co-occurring hashtags
- Ranked list of engaged content/tweets over time
- Geospatial sentiment maps
Experiments ❏ Ask users to define their own narrative units.
❏ Ask users to rank the salience of different narrative units.
❏ Individual trawling around twitter feeds of presidential candidates.
Results ❏ A ranked list of most popular content over time is the most valuable, along with information
on co-occurring hashtags.
❏ Sentiment data is not as helpful because it tends to be inaccurate.
❏ There are tools that exist to do any one of these things, but they are not stitched together for
easy use by operators.
Actions 1. Analyze political campaign dataset for hashtag co-occurrence frequency.
2. Discuss refined MVP and continue to develop new narrative units.
3. Research communication link between awareness and response groups.
Customer Discovery
7. Responses to Narrative Units Presented Previously
A ranked list of
most popular
content over time
A list of
hashtags that
appear with the
same message
with extreme
frequency.
Positive or negative opinion among
geographic or demographic
population.
Narrative Type #1
Narrative Type #2
Narrative Type #3
E.g
Popularitywithusers
Sentiment analysis is thought
to be too crude to provide
useful input. May pollute
signal-noise.
Unit #2 “popular content”
(commonly described as
media like photos or videos)
seemed to be the most
credible. Unit #1 co-occurring
hashtags might provide more
granularity and context than
just single hashtag trends.
8. MVP - 3 Types of “Narratives” Outputted by Our System
A list of hashtags that
appear with the same
message with extreme
frequency.
Positive or negative
opinion among geographic
or demographic
population.
Narrative Type #1 Narrative Type #2
Narrative Type #3
Displayed
to Analysts
Analysts associate
each “narrative unit”
with a real-world,
human-readable
description of a
narrative.
Gain creator: Software automatically
tracks activity of a real-world narratives by
tracking the activity of associated “units”.
Real World Narrative
Long-form, unstructured human description or
collection of info.
A ranked list of most
popular multi-media
content over time
Pain reliever: Social media firehoses
scanned for list of narrative units that match
predefined “schemas”, ranked by frequency.
Problems with this MVP:
● What are the right “units”?
● How is a narrative’s overall growth
calculated from the multiple units with
different sizes? (e.g. relative
“weights?)
Benefits of this MVP:
● Aside from schema, specific units
don’t need to be defined a priori.
● Model allows retroactive reindexing of
a single narrative’s growth based on
new associations.
● Builds a “training set” for more
sophisticated efforts.
9. Mission Model Canvas
- Understand viral potential of
social media posts in real-time.
- Track how groups use
technology over time.
- Gnip/Twitter/Facebook
- CrowdFlower,
Samasource, or
Mechanical Turk
- Pre-existing social
media service and micro-
labor aggregators
- Third-party access
platforms for social
media
-Data visualization (Zoic)
-Content analysis
platforms (Sens.ai,
Leidos)
Primary
ARCYBER
-Bg. General (decision
maker)
-MAJ/LTC/COL
(operational plan)
-Analysts/Operators
(actionable insights)
COCOMs
-General (decision
maker)
-MAJ/LTC/COL
-Analyst/Operator
Secondary
Political Campaigns
-Campaign managers
-Supporters
Consumer Brands
-CMO
-Public Relations Team
- Optimize workflow for
social media analysts.
-Deliver insights to
commanders about
online environment.
-Insights into responses
against specific
broadcasting narratives
-Detect opposition
narratives emerging in
real time
-Early warning on
emerging brand threats
- Customized UI
- Testing with analysts
-Enable faster problem awareness to problem response times for
decision-makers across organizations
- MechanicalTurk or crowdsourcing labor (microtasks)
- UI Development/Testing with ARCYBER analysts.
- Software Development
- Research aggregation? (e.g. Import and reformat existing
knowledge about extremist organizational structure)
- Access to Twitter
firehose or API
- Local language
speaking crowdsourcing
staff.
- Accurate testing for
intercoder reliability
- ARCYBER: Bg. General,
LTC, Strategic Initiatives
Group, OTA, Purchasing PMs,
End-User operator)
-COCOMs: OTA, Operators,
Purchasing PMs
-Political Campaign:
Opposition research team, ???
-Private Sector: CMO, ???
Beneficiaries
Mission AchievementMission Budget/Costs
Buy-In/Support
Deployment
Value
Proposition
Key Activities
Key Resources
Key Partners
10. Value Proposition Canvas - ARCYBER
Products
& Services
Web/Desktop
Application Update research
Customer
Jobs
- New mission priorities.
- Little familiarity with overall
environment.
- No repository for high-level
learnings
Gains
Pains
Gain
Creators
Pain
Relievers
- New opportunities for cyber-
ops
- Social network graph?
-Illustrates evolution of
networks
- Provides insight for
mapping “online terrain”
Visualize information about
how organizations are
using social media
ARCYBER - Operator/Analyst (Actionable Insights)
11. Value Proposition Canvas - ARCYBER
Products
& Services
Web/Desktop
Application
Aggregate insights
from analysts,
compile into plan
passed to decision
maker
- New mission priorities.
- New social media platforms
- Ability to prioritize focus
Customer
Jobs
Gains
Pains
Gain
Creators
Pain
Relievers
-Faster turnaround time with
better data gained from
information awareness software
and technology
- Clear hierarchy of
priorities
ARCYBER - MAJ/LTC/COL (Operational Plans)
-Better data in informing
operational plans provided
to decision makers
-Reducing uncertainty in
operational planning
12. Value Proposition Canvas - ARCYBER
Products
& Services
Web/Desktop
Application
Act on reports and
plans generated
about various cyber
issues across globe
- Little understanding of
ground-level nuances of
challenges
- Little understanding of
proliferating platforms
Customer
Jobs
Gains
Pains
Gain
Creators
Pain
Relievers
- Organizational chart of
technology broken down by
functional purpose
- Timeline-based viewer
- Social network graph?
-Reduce uncertainty of
decision making
-Add methodological rigor
to ARCYBER’s operations
- Accomplish mission
objectives
ARCYBER - Brigadier General (Decision Maker)
13. Value Proposition Canvas - COCOM
Products
& Services
Web/Desktop
Application
Target audience
analysis, finding
opportunities to
optimize influence
operations
Customer
Jobs
-Loss of visibility on key
communicators
- No repository for high-level
learnings
Gains
Pains
Gain
Creators
Pain
Relievers
-Auto-populated list & real-time
visualization
-Illustrates evolution of info
dissemination networks
- Provides insight for mapping
“online terrain”
Closure of visibility gap
COCOM - Operator/Analyst (Actionable Insights)
14. Value Proposition Canvas - COCOM
Products
& Services
Web/Desktop
Application
-Long term
operational planning
- Measuring
effectiveness
Customer
Jobs
- Unclear picture of how
networks evolve, adapt over
time
Gains
Pains
Gain
Creators
Pain
Relievers
- Organizational chart of
technology broken down by
functional purpose
- Visualization of dissemination
networks over time
-Illustrates evolution of info
dissemination networks
- Provides insight for
measuring operations,
mapping “online terrain”
Greater awareness of
network evolution improves
planning, indicators of
operational effectiveness
COCOM - Maj/LTC/Col. (O4-O6) (Operational Plans)
15. Value Proposition Canvas - COCOM
Products
& Services
Web/Desktop
Application
- Judge potential
effect and risk of
operations
- Approve/reject
plans
Customer
Jobs
- Less familiarity with
internet as an operational
environment
- Needs high level summary
of technology use
Gains
Pains
Gain
Creators
Pain
Relievers
- Organizational chart of
technology broken down by
functional purpose
- Timeline-based viewer
-Illustrates evolution of info
dissemination networks
- Provides insight for
mapping “online terrain”
Visualize high-level
information about use
of technology.
COCOM - Brigadier General (O7) (Decision Maker)
16. Value Proposition Canvas - Political Campaign
Products
& Services
Web/Desktop
Application
-Identify opposition
narratives on SM
channels
-Craft responses to
respond w/short
turnaround
Customer
Jobs
-Limited lead time in
anticipating threats from
opposition campaigns
-New stories/themes can
derail campaign momentum
without a targeted response
Gains
Pains
Gain
Creators
Pain
Relievers
-Faster response time to
opposition’s campaigns
-Maintain the initiative in media
environment by rapidly
responding to threats
-Early detection of
emerging opposition
narratives on SM
-Insight into evolving threat
environment
Counter opposition
themes quickly, identify
newly spreading
rumors that could
undermine campaign.
Political Campaigns - Opposition Analysis/Campaign Director
17. Value Proposition Canvas - Consumer Product Company
Products
& Services
Web/Desktop
Application
-Monitor brand
integrity and
customer themes
-Identify and address
emerging problems
Customer
Jobs
-Identify themes about
corporate brand, pinpoint
problem areas early
-Avoid negative narratives
from becoming costly PR or
marketing problems
Gains
Pains
Gain
Creators
Pain
Relievers
-List of customer narratives
about brand that are being
posted online
-Proactive response to
emerging brand threats, better
customer satisfaction
-Early warning about
negative themes
-Identify problem areas,
protect corporate brand
from costly problems
-Protect brand integrity,
create greater
shareholder value by
addressing customer
concerns
Consumer Product Company - CMO/Marketing Organization