Discretionary dissemination on Twitter
Using an unsupervised machine learning approach to analyze 12.8 million tweets posted by S&P 1500 firms from 2012 to 2016, we find that firms tweet more financial information around significantly negative or positive earnings announcements or accounting filings. Specifically, we observe a symmet...
Saved in:
Main Authors: | , , |
---|---|
Format: | text |
Language: | English |
Published: |
Institutional Knowledge at Singapore Management University
2020
|
Subjects: | |
Online Access: | https://ink.library.smu.edu.sg/soa_research/1776 https://ink.library.smu.edu.sg/context/soa_research/article/2803/viewcontent/SSRN_id3105847.pdf |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Singapore Management University |
Language: | English |
id |
sg-smu-ink.soa_research-2803 |
---|---|
record_format |
dspace |
spelling |
sg-smu-ink.soa_research-28032024-11-15T00:32:55Z Discretionary dissemination on Twitter CROWLEY, Richard M. HUANG, Wenli LU, Hai Using an unsupervised machine learning approach to analyze 12.8 million tweets posted by S&P 1500 firms from 2012 to 2016, we find that firms tweet more financial information around significantly negative or positive earnings announcements or accounting filings. Specifically, we observe a symmetric U-shaped relation between the number of financial tweets and the materiality of accounting information events. This relation is consistent with the theoretical prediction in Hummel et al. (2018) which assumes that managers are sensitive to their firm’s fundamental value. We document that this relation also holds for hyperlink usage in tweets about financial information around important events, and that the relation is more pronounced for non-loss firms. Furthermore, our intraday analyses indicate that firms release financial information on Twitter primarily after (before) earnings announcements (10-K or 10-Q filings), suggesting that Twitter plays different roles for firms around separate accounting information events. 2020-08-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/soa_research/1776 info:doi/10.2139/ssrn.3105847 https://ink.library.smu.edu.sg/context/soa_research/article/2803/viewcontent/SSRN_id3105847.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Accountancy eng Institutional Knowledge at Singapore Management University Social Media Discretionary Dissemination Disclosures Twitter Feedback Accounting Corporate Finance Social Media |
institution |
Singapore Management University |
building |
SMU Libraries |
continent |
Asia |
country |
Singapore Singapore |
content_provider |
SMU Libraries |
collection |
InK@SMU |
language |
English |
topic |
Social Media Discretionary Dissemination Disclosures Feedback Accounting Corporate Finance Social Media |
spellingShingle |
Social Media Discretionary Dissemination Disclosures Feedback Accounting Corporate Finance Social Media CROWLEY, Richard M. HUANG, Wenli LU, Hai Discretionary dissemination on Twitter |
description |
Using an unsupervised machine learning approach to analyze 12.8 million tweets posted by S&P 1500 firms from 2012 to 2016, we find that firms tweet more financial information around significantly negative or positive earnings announcements or accounting filings. Specifically, we observe a symmetric U-shaped relation between the number of financial tweets and the materiality of accounting information events. This relation is consistent with the theoretical prediction in Hummel et al. (2018) which assumes that managers are sensitive to their firm’s fundamental value. We document that this relation also holds for hyperlink usage in tweets about financial information around important events, and that the relation is more pronounced for non-loss firms. Furthermore, our intraday analyses indicate that firms release financial information on Twitter primarily after (before) earnings announcements (10-K or 10-Q filings), suggesting that Twitter plays different roles for firms around separate accounting information events. |
format |
text |
author |
CROWLEY, Richard M. HUANG, Wenli LU, Hai |
author_facet |
CROWLEY, Richard M. HUANG, Wenli LU, Hai |
author_sort |
CROWLEY, Richard M. |
title |
Discretionary dissemination on Twitter |
title_short |
Discretionary dissemination on Twitter |
title_full |
Discretionary dissemination on Twitter |
title_fullStr |
Discretionary dissemination on Twitter |
title_full_unstemmed |
Discretionary dissemination on Twitter |
title_sort |
discretionary dissemination on twitter |
publisher |
Institutional Knowledge at Singapore Management University |
publishDate |
2020 |
url |
https://ink.library.smu.edu.sg/soa_research/1776 https://ink.library.smu.edu.sg/context/soa_research/article/2803/viewcontent/SSRN_id3105847.pdf |
_version_ |
1816859135231131648 |