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Research Article | Open Access |

Characterizing the 2016 U.S. Presidential Campaign using Twitter Data

Author 1: Ignasi Vegas Author 2: Tina Tian Author 3: Wei Xiong
International Journal of Advanced Computer Science and Applications (IJACSA) · Vol. 7, No. 10 · Published 2016

DOI: https://doi.org/10.14569/IJACSA.2016.071002

Abstract

This paper models the 2016 U.S. presidential campaign in the context of Twitter. The study analyzes the presidential candidates’ Twitter activity by crawling their real-time tweets. More than 16,000 tweets were observed in this work. We study the interactions between the politicians and their Twitter followers in the retweet and favorite networks. The most frequently mentioned unigrams are presented, which serve the best featuring the political focuses of a candidate. The mention network among the politicians was constructed by parsing the content of their tweets. In this paper, we also study the Twitter profile of the users who follow the presidential candidates. The gender ratio among the Twitter subscribers is examined using the government’s census data. We also investigate the geography of Twitter supporters for each candidate.

Keywords

How to Cite this Article

Vegas, I., Tian, T., & Xiong, W. (2016). Characterizing the 2016 U.S. Presidential Campaign using Twitter Data. International Journal of Advanced Computer Science and Applications, 7(10). https://doi.org/10.14569/IJACSA.2016.071002

Vegas, Ignasi, et al.. "Characterizing the 2016 U.S. Presidential Campaign using Twitter Data." International Journal of Advanced Computer Science and Applications, vol. 7, no. 10, 2016, https://doi.org/10.14569/IJACSA.2016.071002.

@article{Vegas2016,
  title     = {Characterizing the 2016 U.S. Presidential Campaign using Twitter Data},
  journal   = {International Journal of Advanced Computer Science and Applications},
  volume    = {7},
  number    = {10},
  year      = {2016},
  publisher = {The Science and Information Organization},
  author    = {Ignasi Vegas and Tina Tian and Wei Xiong},
  doi       = {10.14569/IJACSA.2016.071002},
  url       = {https://doi.org/10.14569/IJACSA.2016.071002}
}

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