Name
Abstract | ||
|---|---|---|
Twitter is a social network that lets users post their opinions about current affairs, share their social events, and interact with others. Twitter has now become one of the largest sources of news, with over 200 million active users monthly. This paper proposes a method to predict election results based on Twitter data analysis. The method extracts and analyses sentimental information from microblogs to predict the popularity of candidates. The proposed method was used for predicting the result of the 2017 French presidential election. It has been shown that the proposed method significantly outperformed the Tumasjan's method, a well-recognized method for election prediction based on Twitter data. |
Year | DOI | Venue |
|---|---|---|
2017 | 10.1109/CEEC.2017.8101605 | 2017 9th Computer Science and Electronic Engineering (CEEC) |
Keywords | Field | DocType |
Social media analysis,Twitter data analysis,Sentiment analysis,Election prediction | Internet privacy,World Wide Web,Social media,Political science,Social network,Presidential election,Sentiment analysis,Microblogging,Popularity | Conference |
ISSN | ISBN | Citations |
2472-1530 | 978-1-5386-3008-2 | 0 |
PageRank | References | Authors |
0.34 | 5 | 2 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Lei Wang | 1 | 401 | 111.60 |
| John Q. Gan | 2 | 18 | 4.87 |