Twittering Public Sentiments: A Predictive Analysis of Pre-Poll Twitter Popularity of Prime Ministerial Candidates for the Indian Elections 2014
Publication Type:Journal Article
Source:Media watch, Volume 6, Number 2, p.238-254 (2015)
Keywords:Indian Elections 2014, Kejriwal, Modi, Rahul Gandhi, Sentiment analysis, Twitter Analytics, Twitter Engagement Rate.
Twitter is a useful tool for predicting election outcomes, effectively complementing traditional opinion polling. This study undertakes a volume, sentiment and engagement analysis for predicting the popularity of Prime Ministerial candidates on Twitter as a run-up to the Indian Elections 2014. The results from a survey of 2,37,639 pre-poll tweets finds tweet volume as a significant predictor of candidate vote share, and volume and sentiments as predictors for candidate engagement levels. Higher engagement rates evolve from the horizontality of conversations about the candidate, therefore indicating a high degree of interactivity, but do not translate into a higher vote share.
Cite this Research Publication
Related Research Publications
- Simulated and self-sustained classification of Twitter Data based on its sentiment
- AMRITA_CEN-NLP@SAIL2015: Sentiment analysis in indian language using regularized least square approach with randomized feature learning
- Performance evaluation of sentiment classification using query strategies in a pool based active learning scenario
- Exploring sentiment analysis on Twitter data
- AMRITA-CEN@SAIL2015: Sentiment analysis in Indian languages