@inproceedings{cc4e7946ae134bb1b2010ea482a06248,
title = "Tweets and votes: A four-country comparison of volumetric and sentiment analysis approaches",
abstract = "This study analyzes different methodological approaches followed in social media literature and their accuracy in predicting the general elections of four countries. Volumetric and unsupervised and supervised sentiment approaches are adopted for generating 12 metrics to compute predicted vote shares. The findings suggest that Twitter-based predictions can produce accurate results for elections, given the digital environment of a country. A cross-country analyses helps to evaluate the quality of predictions and the influence of different contexts, such as technological development and democratic setups. We recommend future scholars to combine volume, sentiment and network aspects of social media to model voting intentions in developing societies. {\textcopyright} 2016, Association for the Advancement of Artificial Intelligence. All Rights Reserved.",
keywords = "social media, Twitter, elections, predictions",
author = "Saifuddin Ahmed and Kokil Jaidka and Skoric, {Marko M.}",
year = "2016",
month = may,
doi = "10.1609/icwsm.v10i1.14773",
language = "English",
isbn = "9781577357582",
series = "Proceedings of the International AAAI Conference on Web and Social Media",
publisher = "AAAI Press",
number = "1",
pages = "507--510",
booktitle = "Proceedings of the Tenth International AAAI Conference on Web and Social Media (ICWSM 2016)",
note = "10th International AAAI Conference on Web and Social Media (ICWSM 2016) ; Conference date: 17-05-2016 Through 20-05-2016",
}