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The Effects of Twitter Sentiment on Stock Price Returns

Overview of attention for article published in PLoS ONE, September 2015
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About this Attention Score

  • In the top 5% of all research outputs scored by Altmetric
  • High Attention Score compared to outputs of the same age (97th percentile)
  • High Attention Score compared to outputs of the same age and source (97th percentile)

Mentioned by

news
5 news outlets
twitter
51 tweeters
wikipedia
1 Wikipedia page
googleplus
1 Google+ user
reddit
1 Redditor

Citations

dimensions_citation
59 Dimensions

Readers on

mendeley
209 Mendeley
Title
The Effects of Twitter Sentiment on Stock Price Returns
Published in
PLoS ONE, September 2015
DOI 10.1371/journal.pone.0138441
Pubmed ID
Authors

Gabriele Ranco, Darko Aleksovski, Guido Caldarelli, Miha Grčar, Igor Mozetič

Abstract

Social media are increasingly reflecting and influencing behavior of other complex systems. In this paper we investigate the relations between a well-known micro-blogging platform Twitter and financial markets. In particular, we consider, in a period of 15 months, the Twitter volume and sentiment about the 30 stock companies that form the Dow Jones Industrial Average (DJIA) index. We find a relatively low Pearson correlation and Granger causality between the corresponding time series over the entire time period. However, we find a significant dependence between the Twitter sentiment and abnormal returns during the peaks of Twitter volume. This is valid not only for the expected Twitter volume peaks (e.g., quarterly announcements), but also for peaks corresponding to less obvious events. We formalize the procedure by adapting the well-known "event study" from economics and finance to the analysis of Twitter data. The procedure allows to automatically identify events as Twitter volume peaks, to compute the prevailing sentiment (positive or negative) expressed in tweets at these peaks, and finally to apply the "event study" methodology to relate them to stock returns. We show that sentiment polarity of Twitter peaks implies the direction of cumulative abnormal returns. The amount of cumulative abnormal returns is relatively low (about 1-2%), but the dependence is statistically significant for several days after the events.

Twitter Demographics

The data shown below were collected from the profiles of 51 tweeters who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 209 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
United States 3 1%
Switzerland 3 1%
Slovenia 1 <1%
Germany 1 <1%
Brazil 1 <1%
Luxembourg 1 <1%
Japan 1 <1%
Spain 1 <1%
Unknown 197 94%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 43 21%
Student > Master 41 20%
Researcher 29 14%
Student > Bachelor 28 13%
Student > Doctoral Student 17 8%
Other 51 24%
Readers by discipline Count As %
Computer Science 59 28%
Economics, Econometrics and Finance 52 25%
Business, Management and Accounting 38 18%
Unspecified 19 9%
Engineering 13 6%
Other 28 13%

Attention Score in Context

This research output has an Altmetric Attention Score of 85. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 21 March 2018.
All research outputs
#173,408
of 12,689,756 outputs
Outputs from PLoS ONE
#3,584
of 138,161 outputs
Outputs of similar age
#5,193
of 246,331 outputs
Outputs of similar age from PLoS ONE
#121
of 5,610 outputs
Altmetric has tracked 12,689,756 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 98th percentile: it's in the top 5% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 138,161 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 11.8. This one has done particularly well, scoring higher than 97% of its peers.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 246,331 tracked outputs that were published within six weeks on either side of this one in any source. This one has done particularly well, scoring higher than 97% of its contemporaries.
We're also able to compare this research output to 5,610 others from the same source and published within six weeks on either side of this one. This one has done particularly well, scoring higher than 97% of its contemporaries.