Avnit, A. (2009). The Million Followers Fallacy. Internet Draft, Pravda Media. Retrieved from http://tinyurl.com/nshcjg
Budiharto, W., & Meiliana, M. (2018). Prediction and analysis of Indonesia Presidential election from Twitter using sentiment analysis. Journal of Big Data, 5(1), 1–10. https://doi.org/10.1186/s40537-018-0164-1
Cerchiello, P., & Giudici, P. (2016). Big data analysis for financial risk management. Journal of Big Data, 3(1). https://doi.org/10.1186/s40537-016-0053-4
Cerón-Guzmán, J. A., & León-Guzmán, E. (2016). A sentiment analysis system of Spanish tweets and its application in Colombia 2014 presidential election. Proceedings - 2016 IEEE International Conferences on Big Data and Cloud Computing, BDCloud 2016, Social Computing and Networking, SocialCom 2016 and Sustainable Computing and Communications, SustainCom 2016, 250–257. https://doi.org/10.1109/BDCloud-SocialCom-SustainCom.2016.47
Cha, M., & Gummadi, K. P. (2010). Measuring user influence in Twitter: The million follower fallacy. Retrieved from http://en.scientificcommons.org/58470236
Cohen, R., & Ruths, D. (2013). Classifying Political Orientation on Twitter: It’s Not Easy! Seventh International AAAI Conference on Weblogs …, 91–99. Retrieved from http://www.aaai.org/ocs/index.php/ICWSM/ICWSM13/paper/viewFile/6128/6347%5Cnpapers3://publication/uuid/3532F9EA-312A-4F8E-83C3-6369D71D2171
Cury, R. M. (2019). Oscillation of tweet sentiments in the election of João Doria Jr. for Mayor. Journal of Big Data, 6(1), 1–15. https://doi.org/10.1186/s40537-019-0208-1
Dietrich, B. J., & Juelich, C. L. (2018). When presidential candidates voice party issues, does Twitter listen? Journal of Elections, Public Opinion and Parties, 28(2), 208–224. https://doi.org/10.1080/17457289.2018.1441847
Gayo-Avello, D. (2012). No, you cannot predict elections with twitter. IEEE Internet Computing, 16(6), 91–94. https://doi.org/10.1109/MIC.2012.137
Gayo-Avello, D. (2013). A Meta-Analysis of State-of-the-Art Electoral Prediction From Twitter Data. Social Science Computer Review (Vol. 31). https://doi.org/10.1177/0894439313493979
Grimaldi, D. (2019). Can we analyse political discourse using Twitter ? Evidence from Spanish 2019 presidential election. Social Network Analysis and Mining, 1–9. https://doi.org/10.1007/s13278-019-0594-6
Huberty, M. (2015). Can we vote with our tweet? On the perennial difficulty of election forecasting with social media. International Journal of Forecasting, 31(3), 992–1007. https://doi.org/10.1016/j.ijforecast.2014.08.005
Le, H. T., Boynton, G. R., Mejova, Y., Shafiq, Z., & Srinivasan, P. (2017). Revisiting The American Voter on Twitter, 4507–4519. https://doi.org/10.1145/3025453.3025543
Lokers, R., Knapen, R., Janssen, S., van Randen, Y., & Jansen, J. (2016a). Analysis of Big Data technologies for use in agro-environmental science. Environmental Modelling and Software, 84, 494–504. https://doi.org/10.1016/j.envsoft.2016.07.017
Lokers, R., Knapen, R., Janssen, S., van Randen, Y., & Jansen, J. (2016b). Analysis of Big Data technologies for use in agro-environmental science. Environmental Modelling and Software. https://doi.org/10.1016/j.envsoft.2016.07.017
Magalhães, P. C., Aguiar-Conraria, L., & Lewis-Beck, M. S. (2012). Forecasting Spanish elections. International Journal of Forecasting, 28(4), 769–776. https://doi.org/10.1016/j.ijforecast.2012.04.007
Manning, C., & Raghavan, P. . (2009). Introduction to Information Retrieval. Computational Linguistics (Vol. 35). https://doi.org/10.1162/coli.2009.35.2.307
Marozzo, F., & Bessi, A. (2018). Analyzing polarization of social media users and news sites during political campaigns. Social Network Analysis and Mining, 8(1). https://doi.org/10.1007/s13278-017-0479-5
Metaxas, P., & Gayo-Avello, D. (2011). How_(Not)_To_Predict_Elections.pdf. IEEE International Conference on Privacy, Security and Risk.
Molina-González, M. D., Martínez-Cámara, E., Martín-Valdivia, M. T., & Perea-Ortega, J. M. (2013). Semantic orientation for polarity classification in Spanish reviews. Expert Systems with Applications, 40(18), 7250–7257. https://doi.org/10.1016/j.eswa.2013.06.076
O’Connor, B., Balasubramanyan, Routledge, B. R., & Smith, N. A. (2010). From Tweets to Polls: Linking Text Sentiment to Public Opinion Time Series. Proceedings of the Fourth International AAAI Conference on Weblogs and Social Media.
Perboli, G., De Marco, A., Perfetti, F., & Marone, M. (2014). A New Taxonomy of Smart City Projects. Transportation Research Procedia, 3(July), 470–478. https://doi.org/10.1016/j.trpro.2014.10.028
Preoţiuc-Pietro, D., Liu, Y., Hopkins, D., & Ungar, L. (2017). Beyond Binary Labels: Political Ideology Prediction of Twitter Users. Proceedings Ofthe 55th Annual Meeting Ofthe Association for Computational Linguistics, 729–740. https://doi.org/10.18653/v1/p17-1068
Ramteke, J., Shah, S., Godhia, D., & Shaikh, A. (2016). Election result prediction using twitter sentiment analysis. 2016 International Conference on Inventive Computation Technologies (ICICT). https://doi.org/10.1109/inventive.2016.7823280
Shi, L., Agarwal, N., Agrawal, A., Garg, R., & Spoelstra, J. (2012). Predicting US Primary Elections with Twitter, 1–8.
Smith, A., & Rainie, L. (2008). The internet and the 2008 election. Spring.
Tumasjan, A., Sprenger, T. O., Sandner, P. G., & Welpe, I. M. (2011). Election forecasts with Twitter: How 140 characters reflect the political landscape. Social Science Computer Review, 29(4), 402–418. https://doi.org/10.1177/0894439310386557
Villena, J., García, J., Martínez, E., & Jiménez, S. (2015). TASS 2014 - The challenge of aspect-based sentiment analysis. Procesamiento de Lenguaje Natural, 54, 61–68.
Volkova, S., Bachrach, Y., Armstrong, M., & Sharma, V. (2015). Inferring Latent User Properties from Texts Published in Social Media. Proceedings of the Twenty-Ninth Conference on Artificial Intelligence (AAAI), 4296–4297.
Yu, B., Kaufmann, S., & Diermeier, D. (2008). Exploring the characteristics of opinion expressions for political opinion classification. Proceedings of the 2008 International Conference on Digital Government Research, (May), 82–91. Retrieved from http://dl.acm.org/citation.cfm?id=1367832.1367848