Paper Info
Title
Stock market sentiment lexicon acquisition using microblogging data and statistical measures.
Abstract
Lexicon acquisition is a key issue for sentiment analysis. This paper presents a novel and fast approach for creating stock market lexicons. The approach is based on statistical measures applied over a vast set of labeled messages from StockTwits, which is a specialized stock market microblog. We compare three adaptations of statistical measures, such as Pointwise Mutual Information (PMI), two new complementary statistics and the use of sentiment scores for affirmative and negated contexts. Using StockTwits, we show that the new lexicons are competitive for measuring investor sentiment when compared with six popular lexicons. We also applied a lexicon to easily produce Twitter investor sentiment indicators and analyzed their correlation with survey sentiment indexes. The new microblogging indicators have a moderate correlation with popular Investors Intelligence (II) and American Association of Individual Investors (AAII) indicators. Thus, the new microblogging approach can be used alternatively to traditional survey indicators with advantages (e.g., cheaper creation, higher frequencies).
Year
DOI
Venue
2016
10.1016/j.dss.2016.02.013
Decision Support Systems
Keywords
Field
DocType
Sentiment analysis,Stock market,Microblogging data
Data mining,Social media,Sentiment analysis,Computer science,Microblogging,Lexicon,Pointwise mutual information,Stock market
Journal
Volume
Issue
ISSN
85
C
0167-9236
Citations 
PageRank 
References 
22
0.94
33
Authors
3
Name
Order
Citations
PageRank
Nuno Oliveira116015.80
P. Cortez210517.99
Nelson Areal3763.91