Non-textual data and new media sources, Identifying meaningful networks

1. Non-textual data and new
media sources
Identifying meaningful networks

2. Gaining perspective
Volume, speed, credibility – emergent behaviour
• How useful is {near} real-time?
• What makes something meaningful (and to whom)
• Are some events being picked up by mistake
• How do users behave!
Humans Huddle

3. Humans Huddle
“the potential in the era of big data comes not from
drowning in a sea of data but navigating the
most useful ways to derive insight and develop
innovative strategies”.
Leverage relational approaches to
interpret aggregated human
behaviour

4. Tracking information sharing
Social media zeitgeist
Jabhat al-Nusra video propaganda:
• shot on the battle field in Syria,
• uploaded via YouTube
• sharing via Twitter (and others)
Tweeting for the Caliphate: Twitter as a beacon in the new
media zeitgeist. CTC Sentinel 2013 (http://bit.ly/17Aqej9)

5. Open source relational data
66 important Jihadist accounts on Twitter

6. Tracking Response
Information sharing network over time

7. Other sources
• Combining transactional
data
• Is GDELT picking up
‘indicator’ events
• Co-citation or Co-author
networks
• API, RSS, Crawlers, Mapbox

8. Final thought – Reading the signs
Volume, speed, credibility – emergent behaviour
• Aggregated human behaviour
• What makes an action or network
meaningful
• Triangulate via mixed data sources
• (tools such as Maltego3, MongoDB, Gephi, python &
Neo4J)
• Work in genuinely interdisciplinary teams