Name
Title | ||
|---|---|---|
Can twitter analytics predict election outcome? An insight from 2017 Punjab assembly elections |
Abstract | ||
|---|---|---|
Since the beginning of this decade, there has seen an exponential growth in number of internet users using social media, especially Twitter for sharing their views on various topics of common interest like sports, products, politics etc. Due to the active participation of large number of people on Twitter, huge amount of data (i.e. big data) is being generated, which can be put to use (after refining) to analyze real world problems. This paper takes into consideration the Twitter data related to the 2017 Punjab (a state of India) assembly elections and applies different social media analytic techniques on collected tweets to extract and unearth hidden but useful information. In addition to this, we have employed machine learning algorithm to perform polarity analysis and have proposed a new seat forecasting method to accurately predict the number of seats that a political party is likely to win in the elections. Our results confirmed that Indian National Congress was likely to emerge winner and that in fact was the outcome, when results got declared. |
Year | DOI | Venue |
|---|---|---|
2020 | 10.1016/j.giq.2019.101444 | Government Information Quarterly |
Keywords | Field | DocType |
Analytics,Election prediction,Social media,Natural language processing,Machine learning,Sentiment analysis,Twitter | Data science,Economics,Social media,Public relations,Analytics,Big data,Politics,The Internet | Journal |
Volume | Issue | ISSN |
37 | 2 | 0740-624X |
Citations | PageRank | References |
1 | 0.36 | 0 |
Authors | ||
5 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Prabhsimran Singh | 1 | 3 | 1.41 |
| Yogesh Kumar Dwivedi | 2 | 1558 | 97.69 |
| K. S. Kahlon | 3 | 25 | 5.65 |
| Annie Pathania | 4 | 1 | 0.36 |
| Ravinder Singh Sawhney | 5 | 3 | 2.09 |