Analyzing events through the lens of social media
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32nd Subelt conference on Social Networks, organized by International Network for Social Network Analysis.
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Analyzing events through the lens of social media
- 1. Analyzing Events Through the Lens of Social Media Debanjan Mahata (dxmahata@ualr.edu) Nitin Agarwal (nxagarwal@ualr.edu) University of Arkansas at Little Rock This work is supported in part by grants from the US Office of Naval Research (ONR) and US National Science Foundation (NSF)
- 2. Outline • Introduction • Motivation • Challenges • Proposed Framework • Data collection and processing • Experiments- Results and Analysis • Looking Ahead
- 3. Introduction: Socio-Political Events • Tunisia Revolution • Egypt Revolution • Bahrain Protest • Libya Revolution • Morocco Protest • Algeria Protest • Yemen Protest • …, among others.
- 4. Introduction: Economic Events • Spanish Indignants Movements (Spanish protests, 15-M) • #Occupy worldwide
- 5. Introduction: Disaster-related Events • Japan Earthquake & Tsunami • Southeast Asia Floods (crocodile alerts) • Haiti Earthquake
- 6. Social Media’s Influence 2006 2011
- 7. Social Media’s Influence • Social media played a phenomenal role in organizing these events • Citizen journalism at its best
- 8. Goals of the Research • We study how social media can be leveraged to analyze – Events and their characteristics – Coverage differences from mainstream media – Socio-demographic, socio-technical behavioral patterns – and explore further implications of the research
- 9. Challenges • Identifying the right social media sources • Language barrier • Colloquial usage, misspellings, sparse links • Extracting relevant information from the sources – Entity extraction and resolution • Evaluation due to lack of benchmark datasets.
- 10. Challenges C
- 11. Proposed Methodology • Identifying the right social media sources Specificity (κ) of a source ‘S’ for an event ‘E’ IG(E, S) = H (E) − H (E | S) 1 p(s) = ∑ p(e) log − ∑ p(e) e∈E,s∈S p(e, s) log p(e, s) e∈E
- 12. Proposed Methodology • Identifying the right social media sources Closeness (τ) of a term/entity ‘e’ to a source ‘E’ τ = P(e, E) = P(E)P(e | E) P(e | E) = efiEf = ef (e, E)*iEf (e) • Creating Event dictionaries
- 13. Construction of Event Dictionaries • Reference point to Egyptian revolution Tahrir Square, Egyptian specific dictionary government, Gigi construct event vocabulary Ibrahim, Alexandria, • Independent of the sources Wael Abbas, … • Globalvoicesonline.org Libyan revolution specific Tripoli, Muammar Al dictionary Gaddafi, North Atlantic • Extract entities from global Treaty Organization, voices online source Chad, United Kingdom, … • Use closeness measure to Tunisian revolution Tunisian government, Lin order the entities based on specific dictionary Ben Mhenni, Samir Feriani, Kasbah Square, relevance to the event RCD, … – Event-specific dictionary Socio-political (global) Twitter, Iranian – Event category-specific event dictionary Government, Tear gas dictionary devices, Facebook, Big Social network, … Top 5 entities in the event specific and Event category-specific dictionaries
- 14. Data collection • Collected using Google Blog Search • From blogspot.com Event Query Term Number of Blogs Dates Egyptian Revolution “egyptian 579 25th January, 2011 – revolution” OR 7th December, 2011 “egypt protest” Libyan Revolution “libyan revolution” 600 15th February, 2011 OR “libya protest” – 7th December, 2011 Tunisian Revolution “tunisian 484 17th December, revolution” OR 2010 – 7th “tunisia protest” December, 2011
- 15. Data Description Blogger specific Blog post specific Blog specific URL URL URL Timestamp Work information Blogging tags Text Gender Outlinks Blogs followed Topic Category Blogs owned Language
- 16. Source-Entity Distribution: Egyptian Revolution
- 17. Source-Entity Distribution Libyan Revolution Tunisian Revolution
- 18. Validation - Egyptian revolution
- 19. Validation Libyan Revolution Tunisian Revolution
- 20. Rank Comparison Blog Post URL Specificity based Google Search Ranking Engine Ranking http://chinamatters.blogspot.com/2011/03/counterpunch-on- egyptian-revolution.html 1 59 http://happyarabnewsservice.blogspot.com/2011/02/orange-county- womans-role-in-egyptian.html 2 286 http://travel-and-immigration101.blogspot.com/2011/03/travel-news- egypt-tourism-revival.html 3 400 http://travel-and-immigration101.blogspot.com/2011/03/travel-news- egypt-tourism-revival.html 4 277 http://geniusofinsanityworld.blogspot.com/2011/02/egyptian- revolution-vs-iraqi-regime.html 5 55 http://jewssansfrontieres.blogspot.com/2011/03/egyptian-revolution- and-palestine.html 6 202 http://uprootedpalestinians.blogspot.com/2011/01/live-from- egyptian-revolution.html 7 6 http://mespectator.blogspot.com/2011/10/egyptian-revolution- between-citizens.html 8 9 http://yourheartsontheleft.blogspot.com/2011/06/egyptian- revolution-phase-one.html 9 313 http://sohabayoumi.blogspot.com/2011/02/egyptian-revolution- tuesday-february-1.html 10 374
- 21. Scatter plots Tunisian revolution Egyptian revolution Libyan revolution
- 22. Further Analysis: Source Specificity vs. Location All Sources
- 23. Further Analysis: Source Specificity vs. Location Sources localized to Egypt
- 24. Conclusions • Relevance of social media in various events • Methodology to analyze events via social media • Associated challenges • Proposed measures to identify specific sources with respect to atomic information units/entities • Evaluation framework • Popular sources may not be specific • Localized sources tend to be more specific • Expand the dataset, include more and various types of events • Use as apparatus to analyze social movements, collective actions, marketing research, etc.
- 25. Thank You
- 26. Observation • Socio-demographic – Location – Age – Gender – Profession (occupation, industry) – etc. • Socio-technical – Links – Devices – Other social media profiles • Network of bloggers from the extracted data
- 27. Specificity κ = IG(Ei ,Sk ) = H(Ei )− H(Ei ,Sk ) i= n i= n κ = −H (Ei ,Sk ) = ∑ fτ ∑ f i i i i=1 i=1
- 28. Blog Post Url Our Google Search Ranking Engine Ranking http://egyptianchronicles.blogspot.com/2011/0 1 8/libyan-revolution-mermaid-is-liberated.html 13 http://myblog- angeln.blogspot.com/2011/02/citys- 2 old-market-square-taken-over-by.html 329 http://shadowlight9.blogspot.com/2011 /10/revolution-and-democracy-xv- 3 libyan_23.html 9 http://libyanconflict.blogspot.com/20 11/03/were-libyan-rebels-in-zawiyah- 4 defeated.html 194 http://egyptianchronicles.blogspot.com/2011/0 5 8/libyan-revolution-they-are-just-like.html 24 http://realworldrants.blogspot.com/20 11/03/middle-eastafrican- 6 revolutionprotest_21.html 311 http://usahmadawang.blogspot.com/2011 /03/libyas-first-lady-owns-20-tons- 7 of-gold.html 364 http://sincerelyours1.blogspot.com/20 8 11/03/meddling-in-libya.html 204 http://redrave.blogspot.com/2011/08/a fter-collapse-of-gaddafi-regime- 9 where.html 374 http://simonlaub.blogspot.com/2011/02 /libyan-revolution-february-2011- 10 youtube.html 184
- 29. Blog Post Url Our Google Search Engine Ranking Ranking http://mideasti.blogspot.com/2011/01/ president-pm-quit-rcd-does-it- 1 mean.html 162 http://israelmatzav.blogspot.com/2011 /01/surprise-plo-walks-back-support- 2 of.html 40 http://boienwitkowski.blogspot.com/20 3 11/01/part-14.html 420 4 http://machonneuse.blogspot.com/ 459 http://thetunisianrevolution.blogspot .com/2011/02/situation-is-quite- 5 fluid.html 72 http://harakaproject.blogspot.com/201 1/04/force-majeure-how-can-we- 6 curate.html 181 http://youchefayla.blogspot.com/2011/ 7 10/1789-reloaded.html 152 http://rose4hillary.blogspot.com/2011 /02/hillary-clintonwheels-up-for- 8 geneva.html 440 http://ibloga.blogspot.com/2011/01/qa radawi-hails-tunisian-revolution- 9 says.html 99 http://hassanposts.blogspot.com/2011_ 10 01_01_archive.html 174
Notas do Editor
- Middle East and North Africa (MENA) region
- Thailand, Philippines, Cambodia
- 2006 time magazine selected “You” as the person of the year. in 2011. Web 2.0/social media enabled, or more precisely helped people topple decades-old authoritarian regimes in MENA region. Essentially, what people tried to do for the last 40 years social media helped to accomplish that in 5 years.
- Social media has irreversibly transformed how people communicate, organize, mobilize, respond
- Formation of collective action, manifestation of social movements, etc.
- 100s of millions of blogs, billions of tweets, several thousands youtube videos. Tons of region-specific sources. Strictly network-based approaches do not usually perform well.
- Georgian Cyber Campaign (2009) brought Internet traffic to a standstill in the Republic of Georgia. The attacks, which coincided with the Russian military ’s invasion of Georgia, were carried out in large part out by civilians and Russian crime gangs. The attacks were significant in that they made it almost impossible for citizens and officials to communicate about what was happening on the ground during the military operation. According to a US Cyber Consequences Unit (US-CCU) August 2009 special report on this cyber campaign, social networking forums were the primary means used to recruit and arm the attackers. Social media has a key role in monitoring and tracking cyber-threats.
- Chicken and egg problem – to identify good event dictionary you need good source and to identify good source you need event dictionary
- ef-iEf = Generalization of content analysis measure, tf-idf
- Alchemy API used to extract entities Our approach looks at quality (closeness) of the entities and not just quantity, so it is robust to the skewed distribution depicted above.
- Also motivates the need for studying region-specific often non-English language sources.
- In order to select the highly specific sources, we propose a novel ‘specificity’ measure, which estimates the unique information that a source ( S k ) can offer vis-à-vis an event ( E i ). It is important to note here that a source’s specificity is always estimated with respect to a given event. The measure draws upon the theory of information gain and is defined as . Mathematically, where IG(E i , S k ) denotes the information gain for a source related to an event E i , where S k = k th source belonging to ; E i = i th event belonging to ; denotes the set of sources for an event E i , ; denotes the set of events selected for the study; H(E i ) is the total entropy for the event E i , H(E i ,S k ) is the total entropy of the source S k related to the event E i . Since H(E i ) is constant for every event, IG(E i, S k ) is directly proportional to - H(E i , S k ) . So we only calculate the values for H(E i , S k ) in order to find . The formulation of discussed above is generic. Sections 6.3.1 explains a specific implementation.