Polytechnic University of Valencia Congress, CARMA 2016 - 1st International Conference on Advanced Research Methods and Analytics

Font Size: 
Public opinion mining on Sochi-2014 Olympics
Andrei Kirilenko, Svetlana Stepchenkova

Last modified: 27-06-2016

Abstract


The requirements of evidence-based policymaking promote interest to realtime
monitoring of public’s opinions on policy-relevant topics, and social
media data mining allows diversification of information portfolio used by
public administrators. This study discusses issues in public opinion mining
with respect to extraction and analysis of information posted on Twitter
about Sochi-2014 Olympic. It focuses on topics discussed on Twitter and
sentiment analysis of tweets about the Games. Final database contained
613,333 tweets covering time span from November 1, 2013 until March 31,
2014. Using hash tags the data were classified into the following categories:
Events (21%); News (14%); Sports (12%); Anticipation of the Games (12%);
Cheering of the teams (6%) and Problems & Politics (2%). Research reveals
considerable differences in the outcomes of machine sentiment classifiers:
Deeply Moving, Pattern, and SentiStrength. SentiStrength produced the most
suitable results in terms of minimization of incorrectly classified tweets.
Methodological implications and directions for future research are
discussed.

Full Text: PDF