Understanding the predictive power of social media

Internet Research

Volumn 23, Issue 5, 2013, Pages 544-559

  Kalampokis, Evangelos ^a,b   Tambouris, Efthimios ^a,b   Tarabanis, Konstantinos ^a,b  

^a UNIVERSITY OF MACEDONIA   (Greece)

^b INFORMATION TECHNOLOGIES INSTITUTE   (Greece)

Author keywords

Data analysis; Open data; Social networks; World Wide Web

Indexed keywords

EID: 84884999912     PISSN: 10662243     EISSN: None     Source Type: Journal    
DOI: 10.1108/IntR-06-2012-0114     Document Type: Review

References (70)

1. Breiman, L. (2001), "Statistical modeling: the two cultures" in Statistical Science, Vol. 16, No. 3, pp. 199-215.
2. Chen, Y., Wang, Q., Xie, J. (2011), "Online social interactions: a natural experiment on word of mouth versus observational learning" in Journal of Marketing Research, Vol. 48, No. 2, pp. 238-254.
3. Chevalier, J.A., Mayzlin, D. (2006), "The effect of word of mouth on sales: online book reviews" in Journal of Marketing Research, Vol. 43, No. 3, pp. 345-354.
4. Chunara, R., Andrews, J.R., Brownstein, J.S. (2012), "Social and news media enable estimation of epidemiological patterns early in the 2010 Haitian cholera outbreak" in The American Journal of Tropical Medicine and Hygiene, Vol. 86, No. 1, pp. 39-45.
5. Corley, C.D., Cook, D.J., Mikler, A.R., Singh, K.P. (2010), "Text and structural data mining of influenza mentions in web and social media" in International Journal of Environmental Research and Public Health, Vol. 7, No. 2, pp. 596-615.
6. Duan, W., Gu, B., Whinston, A.B. (2008), "Do online reviews matter?-an empirical investigation of panel data" in Decision Support Systems, Vol. 45, No. 4, pp. 1007-1016.
7. Gilbert, E., Karahalios, K. (2009), "Predicting tie strength with social media" in pp. 211-220, 27th International Conference on Human Factors in Computing Systems-CHI, pp.
8. Konishi, S., Kitagawa, G. (2007), Information Criteria and Statistical Modeling, Springer, New York, NY.
9. Louis, C. St, Zorlou, G. (2012), "Can twitter predict disease outbreaks?" in British Medical Journal, Vol. 344, p. e235.
10. Morales-Arroyo, M., Pandey, T. (2010), "Identification of critical eWOM dimensions for music albums" in pp. 1230-1235, IEEE International Conference on Management of Innovation and Technology, IEEE, pp.
11. Oghina, A., Breuss, M., Tsagkias, M., de Rijke, M. (2012), "Predicting IMDB movie rating using social media" in pp. 503-507, 34th European Conference on Information Retrieval (ECIR), Springer, pp.
12. Reinstein, D., Snyder, C.M. (2005), "The influence of expert reviews on consumer demand for experience goods: a case study of movie critics" in Journal of Industrial Economics, Vol. 53, No. 1, pp. 27-51.
13. Shmueli, G., Koppius, O.R. (2011), "Predictive analytics in information systems research" in MIS Quarterly, Vol. 35, No. 3, pp. 553-572.
14. Strong, D.M., Lee, Y.W., Wang, R.Y. (1997), "Data quality in context" in Communications of the ACM, Vol. 40, No. 5, pp. 103-110.
15. Tsagkias, E., Weerkamp, W., de Rijke, M. (2010), "News comments: exploring, modeling, and online predicting" in pp. 191-203, ECIR, Springer, pp.
16. Webster, J., Watson, R.T. (2002), "Analyzing the past to prepare for the future: writing a literature review" in MIS Quarterly, Vol. 26, No. 2, pp. xiii-xxiii.
17. Ye, Q., Law, R., Gu, B. (2009), "The impact of online user reviews on hotel room sales" in International Journal of Hospitality Management, Vol. 28, No. 1, pp. 180-182.
18. Achrekar, H., Gandhe, A., Lazarus, R., Yu, S.-H., Liu, B. (2011), "Predicting flu trends using twitter data" in pp. 702-707, IEEE Conference on Computer Communications Workshops, IEEE, pp.
19. Althouse, B.M., Ng, Y.Y., Cummings, D.A.T. (2011), "Prediction of dengue incidence using search query surveillance" in Public Library of Science, Vol. 5, No. 8, pp. 1-7.
20. Antweiler, W., Frank, M.Z. (2004), "Is all that talk just noise? The information content of internet stock message boards" in Journal of Finance, Vol. 59, No. 3, pp. 1259-1294.
21. Asur, S., Huberman, B.A. (2010), "Predicting the future with social media" in pp. 492-499, IEEE/WIC/ACM International Conference on Web Intelligence and Intelligent Agent Technology, IEEE Press, pp.
22. Bollen, J., Mao, H., Zeng, X.J. (2011), "Twitter mood predicts the stock market" in Journal of Computational Science, Vol. 2, No. 1, pp. 1-8.
23. Bordino, I., Battiston, S., Caldarelli, G., Cristelli, M., Ukkonen, A., Weber, I. (2012), "Web search queries can predict stock market volumes" in PLoS ONE, Vol. 7, No. 7, p. e40014.
24. Bothos, E., Apostolou, D., Mentzas, G. (2010), "Using social media to predict future events with agent-based markets" in IEEE Intelligent Systems, Vol. 25, No. 6, pp. 50-58.
25. Choi, H., Varian, H. (2012), "Predicting the present with Google trends" in The Economic Record, Vol. 88, S1, pp. 2-9.
26. Culotta, A. (2010), "Towards detecting influenza epidemics by analyzing Twitter messages" in pp. 115-122, First Workshop on Social Media Analytics, 25-28 July, ACM Press, Washington, DC, pp.
27. Da, Z., Engelberg, J., Gao, P. (2011), "In search of attention" in The Journal of Finance, Vol. 66, No. 5, pp. 1461-1499.
28. De Choudhury, M., Sundaram, H., John, A., Seligmann, D.D. (2008), "Can blog communication dynamics be correlated with stock market activity?" in pp. 55-60, 19th ACM Conference on Hypertext and Hypermedia, ACM Press, pp.
29. Earle, P., Bowden, D.C., Guy, M. (2011), "Twitter earthquake detection: earthquake monitoring in a social world" in Annals of Geophysics, Vol. 54, No. 6, pp. 708-715.
30. Ettredge, M., Gerdes, J., Karuga, G. (2005), "Using web-based search data to predict macro-economic statistics" in Communications of the ACM, Vol. 48, No. 11, pp. 87-92.
31. Forman, C., Ghose, A., Wiesenfeld, B. (2008), "Examining the relationship between reviews and sales: the role of the reviewer identity disclosure in electronic markets" in Information Systems Research, Vol. 19, No. 3, pp. 291-313.
32. Franch, F. (2013), "(Wisdom of the crowds)2: 2010 UK election prediction with social media" in Journal of Information Technology & Politics, Vol. 10, No. 1, pp. 57-71.
33. Gayo-Avello, D. (2011), "Don't turn social media into another 'Literary Digest' poll" in Communications of the ACM, Vol. 54, No. 10, pp. 121-128.
34. Ghose, A., Ipeirotis, P.G. (2011), "Estimating the helpfulness and economic impact of product reviews: mining text and reviewer characteristics" in IEEE Transactions on Knowledge and Data Engineering (TKDE), Vol. 23, No. 10, pp. 1498-1512.
35. Gilbert, E., Karahalios, K. (2010), "Widespread worry and the stock market" in pp. 58-65, Fourth International Conference on Weblogs and Social Media, AAAI Press, pp.
36. Ginsberg, J., Mohebbi, M.H., Patel, R.S., Brammer, L., Smolinski, M.S., Brilliant, L. (2009), "Detecting influenza epidemics using search engine query data" in Nature, Vol. 457, No. 7232, pp. 1012-1014.
37. Goel, S., Hofman, J.M., Lahaie, S., Pennock, D.M., Watts, D.J. (2010), "Predicting consumer behaviour with web search" in Proceedings of the National Academy of Sciences (PNAS), Vol. 107, No. 41, pp. 17486-17490.
38. Gruhl, D., Guha, R., Kumar, R., Novak, J., Tomkins, A. (2005), "The predictive power of online chatter" in pp. 78-87, Eleventh ACM SIGKDD International Conference on Knowledge Discovery in Data Mining, ACM Press, pp.
39. Guzman, G. (2011), "Internet search behavior as an economic forecasting tool: the case of inflation expectations" in Journal of Economic and Social Measurement, Vol. 36, No. 3, pp. 119-167.
40. He, Y., Saif, H., Wei, Z., Wong, K. (2012), "Quantising opinions for political tweets analysis" in pp. 3901-3906, Eight International Conference on Language Resources and Evaluation, European Language Resources Association, pp.
41. Hulth, A., Rydevik, G., Linde, A. (2009), "Web queries as a source for syndromic surveillance" in PLoS ONE, Vol. 4, No. 2, p. e4378.
42. Jin, X., Gallagher, A., Cao, L., Luo, J., Han, J. (2010), "The wisdom of social multimedia: using flickr for prediction and forecast" in pp. 1235-1244, ACM Multimedia 2010, ACM Press, pp.
43. Jungherr, A., Jurgens, P., Schoen, H. (2012), "Why the pirate party won the German election of 2009 or the trouble with predictions: a response to Tumasjan, A., Sprenger, T.O., Sander, P.G. and Welpe, I.M. 'predicting elections with twitter: what 140 characters reveal about political and sentiment'" in Social Science Computer Review, Vol. 30, No. 2, pp. 229-234.
44. Krauss, J., Nann, S., Simon, D., Fischbach, K., Gloor, P. (2008), "Predicting movie success and academy awards through sentiment and social network analysis" in pp. 2026-2037, 16th European Conference on Information Systems, pp.
45. Lampos, V., Cristianini, N. (2012), "Nowcasting events from the social web with statistical learning" in ACM Transactions on Intelligent Systems and Technology, Vol. 3, No. 4, pp. 72:1-72:22.
46. Liu, Y., Huang, X., An, A., Yu, X. (2007), "ARSA: a sentiment-aware model for predicting sales performance using blogs" in pp. 607-614, 30th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, ACM Press, pp.
47. Liu, Y., Chen, Y., Lusch, R.F., Chen, H., Zimbra, D., Zeng, S. (2010), "User-generated content on social media: predicting market success with online word-of-mouth" in IEEE Intelligent Systems, Vol. 25, No. 1, pp. 75-78.
48. Livne, A., Simmons, P.S., Adar, E., Adamic, L.A. (2011), "The party is over here: structure and content in the 2010 election" in pp. 201-208, Fifth International AAAI Conference on Weblogs and Social Media, AAAI Press, pp.
49. Lui, C., Metaxas, P.T., Mustafaraj, E. (2011), "On the predictability of the US Elections through search volume activity" in pp. 165-172, IADIS International Conference e-Society, pp.
50. Metaxas, P.T., Mustafaraj, E., Gayo-Avello, D. (2011), "How (not) to predict election" in pp. 165-171, IEEE Third International Conference on Social Computing, IEEE, pp.
51. Mishne, G., Glance, N. (2006), "Predicting movie sales from blogger sentiment", American Association for Artificial Intelligence 2006 Spring Symposium on Computational Approaches to Analysing Weblogs, Stanford University in Stanford, CA, 27-29 March.
52. O'Connor, B., Balasubramanyan, R., Routledge, B.R., Smith, N.A. (2010), "From tweets to polls: linking text sentiment to public opinion time series" in pp. 122-129, Proceedings of the International AAAI Conference on Weblogs and Social Media, AAAI Press, pp.
53. Oh, C., Sheng, O. (2011), "Investigating predictive power of stock micro blog sentiment in forecasting future stock price directional movement" in p. 17, 32nd International Conference on Information Systems, AIS, p.
54. Polgreen, P.M., Chen, Y., Pennock, D.M., Nelson, F.D. (2008), "Using internet searches for influenza surveillance" in Clinical Infectious Diseases, Vol. 47, No. 11, pp. 1443-1448.
55. Ritterman, J., Osborne, M., Klein, E. (2009), "Using prediction markets and twitter to predict a swine flu pandemic" in pp. 9-17, First International Workshop on Mining Social Media, 9 November, Sevilla, pp.
56. Rui, H., Whinston, A. (2011), "Designing a social-broadcasting-based business intelligence system" in ACM Transactions on Management Information Systems, Vol. 2, No. 4, pp. 22:1-22:19.
57. Sakaki, T., Okazaki, M., Matsuo, Y. (2010), "Earthquake shakes twitter users: real-time event detection by social sensors" in pp. 851-860, 19th International Conference on World Wide Web (WWW'10), ACM Press, pp.
58. Signorini, A., Segre, A.M., Polgreen, P.M. (2011), "The use of twitter to track levels of disease activity and public concern in the US during the influenza A H1N1 pandemic" in PLoS ONE, Vol. 6, No. 5, p. e19467.
59. Skoric, M., Poor, N., Achananuparp, P., Lim, E., Jiang, J. (2012), "Tweets and votes: a study of the 2011 Singapore General Election" in pp. 2583-2591, 45th Hawaii International Conference on System Sciences, IEEE, pp.
60. Tjong, E., Sang, K., Bos, J. (2012), "Predicting the 2011 Dutch senate election results with twitter" in pp. 53-60, 13th Conference of the European Chapter of the Association for Computational Linguistics, Association for Computational Linguistics, pp.
61. Tumasjan, A., Sprenger, T.O., Sandner, P.G., Welpe, I.M. (2010), "Predicting elections with twitter: what 140 characters reveal about political sentiment" in pp. 178-185, Fourth International AAAI Conference on Weblogs and Social Media, AAAI Press, pp.
62. Tumasjan, A., Sprenger, T.O., Sandner, P.G., Welpe, I.M. (2012), "Where there is a sea there are pirates: response to Jungherr, Jurgens, and Schoen" in Social Science Computer Review, Vol. 30, No. 2, pp. 235-239.
63. Vosen, S., Schmidt, T. (2011), "Forecasting private consumption: survey-based indicators vs Google trends" in Journal of Forecasting, Vol. 30, No. 6, pp. 565-578.
64. Vosen, S., Schmidt, T. (2012), "A monthly consumption indicator for Germany based on internet search query data" in Applied Economics Letters, Vol. 19, No. 7, pp. 683-687.
65. Wang, X., Gerber, M.S., Brown, D.E. (2012), "Automatic crime prediction using events extracted from twitter posts" in Yang, S.J., Greengerg, A.M. and Endsley, M. (Eds.), SBP 2012, LNCS 7227, Springer-Verlag, Berlin Heidelberg, pp. 231-238.
66. Wilson, K., Brownstein, J.S. (2009), "Early detection of disease outbreaks using the internet" in Canadian Medical Association Journal, Vol. 180, No. 8, pp. 829-831.
67. Wu, L., Brynjolfsson, E. (2009), "The future of prediction: how google searches foreshadow housing prices and quantities", 30th International Conference on Information Systems, AISE, available at: http://aisel.aisnet.org/icis2009/147 (accessed February 2012).
68. Zhang, X., Fuehres, H., Gloor, P.A. (2011), "Predicting stock market indicators through twitter 'I hope it is not as bad as I fear'" in Procedia-Social and Behavioral Sciences, Vol. 26, pp. 55-62.
69. Zhang, X., Fuehres, H., Gloor, P.A. (2012), "Predicting asset value through twitter buzz" in Altmann, J. (Ed.), Advances in Collective Intelligence, pp. 23-34, AISC 113, Springer Berlin Heidelberg, pp.
70. Shmueli, G. (2010), "To explain or to predict?" in Statistical Science, Vol. 25, No. 3, pp. 289-310.