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CPRsouth 2016 Zanzibar PIZZA TO POLICY: Social Media Analytics of a Pizza and implications for policy making Ashish Rathore IIT Delhi, INDIA [email protected] Research Question • How does the usage of social media provide valuable insights to businesses in developing new products? • How to identify the patterns and trends emerging in Twitter data for a new product? • How can network analysis help businesses in identifying lead users and their influence? • Whether social media analytics can be used for policy making? Social Media Definitions“…..group of Internet-based applications that build on the ideological and tech. foundations of Web 2.0, and that allow the creation and exchange of User Generated Content (UGC)” (Kaplan & Haenlein, 2010) • “…..essential sources of online communications and contents sharing, influences, observations, subjectivity, assessments, approaches, evaluation , feelings, opinions and sentiments expressions” (Naaman, 2010) Social Media Web 2.0 UGC Social Media Content Network Social Media in Product Development Customers (Thoughts, Emotions) UGC Businesses (New Product Development) Ashish 4 Methodology • Social Network Site (Twitter) • Text Mining and Extraction Data Preprocessing Data Analysis • Topic detection and Clustering • Sentiment analysis • Community Detection • Network analysis • Graphs Data Visualization Social Media Platform: Twitter Tools: R (Open Source) & NodeXL Search Term: Dominos Italian Exotic Pizza Data Size: 52,552 tweets (Pre-launch) & 63,165 tweets (Post-launch) Ashish 5 Results, Analysis & Discussion Domain Clustering upcoming Pre-launch Post-launch existing Word Frequency Comparative view of words with others Pre-launch Post-launch Cont.. • order, easi, place, • tweet, order, job, effect, tweet, job, hire, welcome, free, delivery, delivery, gift, card, custom, service, want, sugar, sweet place, edit, return, get, like, new, look • pizza order time,order easydeliveryhire, and to order, specific places, • delivery, start tweet, get services, new pizza welcome notes from free service, job hire, appearance, taste of return delivery the company, girt cards, look rep, the new pizza, the jobs hiring in Dominos of engagement and sweet sugarway about by tweeting and job pizza opportunity Ideation Word Network based on the degree counts Pre-launch Post-launch Directional Word Network Pre-launch Post-launch Hierarchy of Words Thematic Analysis Pre-launch Post-launch Sentiment Analysis • Emotion Classification Pre-launch Post-launch Time Series Sentiment Analysis Word Sentiment Categorization Pre-launch Post-launch Community Detection Pre-launch Post-launch Cont.. Community Evolvement Implication • • • • UGC / customers’ reactions for design To gauge product success/failure Approach of collecting data requires relatively low cost Community helps in understanding target audience and their collective judgement – transfer of effective information from public community to policymakers based on localized similar interests and behaviors Policy Recommendations • Methodology extended for policy arena • Social media data inputs for policy making – GST in India – Transport policy using travellers’ views and experiences – In disaster emergencies, harvesting information for situation awareness and taking actions – Rumours & Social unrest REFERENCES Adedoyin-Olowe, M., Gaber, M. M. & Stahl, F. (2013). A survey of data mining techniques for social network analysis. Retrieved October 7, 2014, from http://jdmdh.episciences.org/18/pdf Banerjee, N., Chakraborty, D., Joshi, A., Mittal, S., Rai, A., &Ravindran, B. (2012, May). 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Community detection in social media. Data Mining and Knowledge Discovery,24(3), 515-554. Sam, Y., &Cai, Y. (2015). A Study on the Use of Social Media to Understand Consumer Preference: The Case of Starbucks. International Journal of Management and Business Research, 5(3), 207-214. Thelwall, M., Buckley, K., &Paltoglou, G. (2011). Sentiment in Twitter events.Journal of the American Society for Information Science and Technology,62(2), 406-418. Tuten, T. L., and Solomon, M. R. (2013). Social Media Marketing. Boston: Pearson. Verhoef, P. C., Beckers, S. F., & van Doorn, J. (2013). Understand the perils of co-creation.Harvard Business Review, 91(9), 28. Thanks You! Q&A Pre-launch Post-launch Pre-launch Post-launch