Sentiment Aggregate Functions for Political Opinion Polling using Microblog Streams

• Type: Article in International Conference Proceedings Book
• Date: 2016

Authors

Saleiro, P (Author) Other; Gomes, L (Author) Other; Carlos Soares (Author) FEUP

Conference proceedings International

Title: ACM International Conference Proceeding Series

Pages: 44-50

9th International C* Conference on Computer Science and Software Engineering, C3S2E 2016

20 July 2016 through 22 July 2016

Indexing

Scopus - 10 Citations

Other information

Authenticus ID: P-00K-KHN

DOI: 10.1145/2948992.2949022

Abstract (EN): The automatic content analysis of mass media in the social sciences has become necessary and possible with the raise of social media and computational power. One particularly promising avenue of research concerns the use of sentiment analysis in microblog streams. However, one of the main challenges consists in aggregating sentiment polarity in a timely fashion that can be fed to the prediction method. We investigated a large set of sentiment aggregate functions and performed a regression analysis using political opinion polls as gold standard. Our dataset contains nearly 233 000 tweets, classified according to their polarity (positive, negative or neutral), regarding the five main Portuguese political leaders during the Portuguese bailout (2011-2014). Results show that different sentiment aggregate functions exhibit different feature importance over time while the error keeps almost unchanged. © 2016 ACM.

Language: English

Type (Professor's evaluation): Scientific