Abstract
Twitter is among the most popular social networking Web sites today [1], with approximately 317 million monthly active users (Quarter 3 2016). Of these, 67 million users are from the USA. Twitter being a micro-blogging platform is widely used by people to express their opinions. Approximately, 500 million tweets are posted in a day, which is around 6000 tweets per second. Assuming, even one-tenth of these tweets reflect an emotion that results in a lot of people-generated data, which can prove to be a treasure trove of information if studied carefully. We intend to perform sentimental analysis on Twitter data of the US Presidential Election 2016 and then overlay our findings with respect to the two main candidates: Hillary Clinton and Donald Trump with the actual election result, to be able to categorically state whether Twitter can be used as a proper indication of any election.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Similar content being viewed by others
References
Liu, Y., Kliman-Silver, C., Mislove, A.: The tweets they are a-Changin: evolution of twitter users and behavior. In: ICWSM, vol. 30, pp. 5–314 (2014)
Tumasjan, A., Sprenger, T.O., Sandner, P.G., Welpe, I.M.: Predicting elections with twitter: what 140 characters reveal about political sentiment. In: ICWSM, vol. 10(1), pp. 178–185 (2010)
Tumasjan, A., Sprenger, T.O., Sandner, P.G., Welpe, I.M.: Election forecasts with Twitter: how 140 characters reflect the political landscape. Soc. Sci. Comput. Rev. 29(4), 402–418 (2011)
Makice, K.: Twitter API: Up and Running: Learn How to Build Applications with the Twitter API. O’Reilly Media, Inc. (2009)
Agarwal, A., Xie, B., Vovsha, I., Rambow, O., Passonneau, R.: Sentiment analysis of twitter data. In: Proceedings of the Workshop on Languages in Social Media. Association for Computational Linguistics, pp. 30–38
Chin, D., Zappone, A., Zhao, J.: Analyzing Twitter Sentiment of the 2016 Presidential Candidates (2016)
Wang, Y., Li, Y., Luo, J.: Deciphering the 2016 US Presidential Campaign in the Twitter Sphere: A Comparison of the Trumpists and Clintonists. arXiv preprint arXiv:1603.03097 (2016)
Kumar, A., Sebastian, T.M.: Sentiment analysis on twitter. IJCSI Int. J. Comput. Sci. Issues 9(3), 372–378 (2012)
Taboada, M., Brooke, J., Tofiloski, M., Voll, K., Stede, M.: Lexicon-based methods for sentiment analysis. Comput. Linguist. 37(2), 267–307 (2011)
Author information
Authors and Affiliations
Corresponding author
Editor information
Editors and Affiliations
Rights and permissions
Copyright information
© 2020 Springer Nature Singapore Pte Ltd.
About this paper
Cite this paper
Somula, R., Dinesh Kumar, K., Aravindharamanan, S., Govinda, K. (2020). Twitter Sentiment Analysis Based on US Presidential Election 2016. In: Satapathy, S., Bhateja, V., Mohanty, J., Udgata, S. (eds) Smart Intelligent Computing and Applications . Smart Innovation, Systems and Technologies, vol 159. Springer, Singapore. https://doi.org/10.1007/978-981-13-9282-5_34
Download citation
DOI: https://doi.org/10.1007/978-981-13-9282-5_34
Published:
Publisher Name: Springer, Singapore
Print ISBN: 978-981-13-9281-8
Online ISBN: 978-981-13-9282-5
eBook Packages: Intelligent Technologies and RoboticsIntelligent Technologies and Robotics (R0)