A glimpse into what social media is all about and how the researchers in the world are using social media. Social media is not a mere hype and not a platform to leverage word-of-the-mouth practices as is the common perception of it in Pakistan: it is much more than that and this is what this talk presented.

1. Social MEDIA MINING AND ANALYTICS A Look into Social Media from a Scientific Perspective 1 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

2. Introduction What is Social Media? 2 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

3. Introduction Social media is the hot thing in town. Everyone wants to do it. No one actually knows how. (AvinashKaushik, Google’s analytics evangelist) 3 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

4. Introduction Social Media is not only about Social Networks 4 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

5. Introduction Social Media is a media for social interaction using highly accessible and scalable communication techniques. Social Media is the use of web-based and mobile technologies to turn communications into interactive dialog. - Wikipedia 5 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

6. Introduction “In contrast to one-to-many communication structure of traditional mass-media, social media allows the emergence of many-to-many communication, and gives rise to a mass of self-communication” [Castells, 2009] 6 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

7. Social Media Examples Social communication: emails, mobiles, forums, chats Social networking: facebook, google+ Social blogging/microblogging: twitter, livejournal, blogger Social sharing: flickr, vimeo, youtube Social news: digg, slashdot, cnn, ireport Social bookmarking: delicious, citulike Social knowledge/wikis: wikipedia, tripadvisor Social shopping: groupon, amazon, ebay Social apps and games: foursquare, farmville 7 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

8. Social Media Challenge Too much data! 8 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

9. Social Media Goals What could we do? Ask the right questions 9 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

10. Questions Why social media? What is social media for? Social Media Policies and Strategies What is going on? What can we learn? How to exploit social media? Social Media Mining Social Media Practices 10 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

11. Talk Organization Graph Mining Opinion Mining and Sentiment Analysis Smart Mobility Social Media Engagement and Social Innovations 11 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

12. Graph Mining 12 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

13. Graph Mining: Introduction Social Media  social presence, social interactions Graph G=G(V,E) V is the set of vertices, or nodes E is the set of edges which may or may not have weights 13 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

14. Example ‘user user’ graphs on the base of social interactions (e.g. friendship, communications: sharing, commenting) 14 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

15. Example ‘user properties’ bipartitegraphs 15 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

16. Quiz 16 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

17. Quiz 17 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

18. What is the difference? 18 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

19. Power Law Power law is a special family of distributions Human heights City population No. of books sold 19 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

20. Power Law Random variable X has a power law distribution with exponent α: P (X>x) ~ x-αas x∞ Pareto principle: for many events roughly 80% of the effects come from 20% of the causes 20 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

21. Power Law: Research On Twitter Characteristics The number of followings (solid line) and that of followers (dotted line) on Twitter [Kwak et al., 2010] 21 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

22. Social Media Effects on Traditional Media [An et al., 2011] Social media changes the ways in which people Read news Share news Interact on news items “News no longer breaks, it tweets” 22 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

23. Media Graph Mining Results: Computational Journalism Journalists are playing prominent role in social media Audience interaction Personal update 11K 23 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

24. Media Graph Mining Results: Media Publishers Reach More Audience Yes: Social interaction increases publisher’s audience On average, audience size increases by a factor of 28 24 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

25. Media Graph Mining Results: Users Exposed to Diverse Opinions Yes: Users are exposed to diverse opinions through social interactions 25 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

26. Opinion Mining and Sentiment Analysis 26 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

27. Terminology and Problems Sentiment analysis aka opinion mining is the task of automatically detecting sentiment in text Active research area since 2002 Standard part of online market research toolkits Opinions are personal judgements about something It is good. It is bad. It is expensive. Subjective text contains opinions; Objective text states only facts. Sentiments are expressions of emotion or attitude or opinion It is good. It is bad. I like it. I am happy. I am depressed. I am angry at you. Sentiment analysis is often thought of as the prediction of people’s private/internal states from text 27 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

28. Commercial Sentiment Analysis Goals Determine overall opinions about a product E.g, the M90 phone is excellent E.g., the M90 phone is expensive but excellent Determine opinions about parts of a product E.g., the screen of the M90 is too small but its weight is very light I love the steering wheel on the new Picasso 28 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

29. Commercial Sentiment Analysis Goals Determine changes in overall customer brand opinion (e.g. daily proportions of positive/negative comments) In response to advertising As routine monitoring Identify individual unhappy customers E.g., identify Tweets that mention the brand and are negative 29 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

30. Social Science Sentiment Analysis Goals Track trends in sentiment over time Identify changes in sentiment Discover patterns in sentiment use in a communicaton medium E.g, gender, age, nationality differences Do women/Russians use more sentiment? 30 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

31. Smart Mobility 31 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

32. Tesco – Home Plus Korea Case 32 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

33. Social Media Engagement and Social Innovations 33 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

34. New Directions First International Workshop on Social Media Engagement (SoME011, in conjunction with WWW2011) Engagement defines the phenomena of being captivated and motivated. Engagement can be measured in terms of a single interactive session or of a more long-term relationship with the social platform across multiple interactions. To design not just systems, but rather engaging experiences. [Attfield et al., 2011] “Towards a science of user engagement ”. 34 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

35. Engagement and Development How to use social media to focus on social problems? And how to make social media available for the people who generally do not have access to the Internet? 35 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

36. Social Networks for Agro-Produce Marketing Research by DhirubhaiAmbani Institute of Information and Communication Technology Use of social network platform such as Twitter for agro-produce marketing: A platform for farmers to sell their product(s) and merchants to buy agro-produce and re-sell in the market. Collected tweets from sellers and buyers can be used to generate classified summarized information 36 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

37. Applications 37 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011

38. Applications of Social Media Analytics https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011 38 Startups built around Social Media Analytics: Thriving Business Model SocialFlow Social Media Optimization Platform Works in Domains of Viral and Word-of-Mouth Marketing Provides Services to Major Media Outlets Recent study How different audiences consumed and rebroadcast messages news organizations were sending out: AlJazeera English, BBC News, CNN, The Economist, Fox News and New York Times

39. Applications of Social Media Analytics https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011 39 Startups built around Social Media Analytics: Thriving Business Model SocialFlow Social Media Optimization Platform Works in Domains of Viral and Word-of-Mouth Marketing Provides Services to Major Media Outlets Recent study How different audiences consumed and rebroadcast messages news organizations were sending out: AlJazeera English, BBC News, CNN, The Economist, Fox News and New York Times

40. Applications of Social Media Analytics https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011 40 Social Media within Military and Defence The Pentagon sees the advances in Social Media as the new battlefield, and something that needs to be looked at to track the information being provided about military operations on the web.

41. Applications of Social Media Analytics https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011 41 Election Campaigns

42. Thank You Reach me on Twitter: @ArjumandYounus Email me: ayounus@iba.edu.pk 42 https://www.facebook.com/WebSTIBA Twitter: #csibaseminar2011