社会信号

IF 10.4 1区 经济学 Q1 BUSINESS, FINANCE
J. Anthony Cookson , Runjing Lu , William Mullins , Marina Niessner
{"title":"社会信号","authors":"J. Anthony Cookson ,&nbsp;Runjing Lu ,&nbsp;William Mullins ,&nbsp;Marina Niessner","doi":"10.1016/j.jfineco.2024.103870","DOIUrl":null,"url":null,"abstract":"<div><p>We examine social media attention and sentiment from three major platforms: Twitter, StockTwits, and Seeking Alpha. We find that, even after controlling for firm disclosures and news, attention is highly correlated across platforms, but sentiment is not: its first principal component explains little more variation than purely idiosyncratic sentiment. Using market events, we attribute differences across platforms to differences in users (e.g., professionals versus novices) and differences in platform design (e.g., character limits in posts). We also find that sentiment and attention contain different return-relevant information. Sentiment predicts positive next-day returns, but attention predicts negative next-day returns. These results highlight the importance of considering both social media sentiment and attention, and of distinguishing between different investor social media platforms.</p></div>","PeriodicalId":51346,"journal":{"name":"Journal of Financial Economics","volume":"158 ","pages":"Article 103870"},"PeriodicalIF":10.4000,"publicationDate":"2024-06-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The social signal\",\"authors\":\"J. Anthony Cookson ,&nbsp;Runjing Lu ,&nbsp;William Mullins ,&nbsp;Marina Niessner\",\"doi\":\"10.1016/j.jfineco.2024.103870\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><p>We examine social media attention and sentiment from three major platforms: Twitter, StockTwits, and Seeking Alpha. We find that, even after controlling for firm disclosures and news, attention is highly correlated across platforms, but sentiment is not: its first principal component explains little more variation than purely idiosyncratic sentiment. Using market events, we attribute differences across platforms to differences in users (e.g., professionals versus novices) and differences in platform design (e.g., character limits in posts). We also find that sentiment and attention contain different return-relevant information. Sentiment predicts positive next-day returns, but attention predicts negative next-day returns. These results highlight the importance of considering both social media sentiment and attention, and of distinguishing between different investor social media platforms.</p></div>\",\"PeriodicalId\":51346,\"journal\":{\"name\":\"Journal of Financial Economics\",\"volume\":\"158 \",\"pages\":\"Article 103870\"},\"PeriodicalIF\":10.4000,\"publicationDate\":\"2024-06-03\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of Financial Economics\",\"FirstCategoryId\":\"96\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S0304405X2400093X\",\"RegionNum\":1,\"RegionCategory\":\"经济学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"BUSINESS, FINANCE\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Financial Economics","FirstCategoryId":"96","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S0304405X2400093X","RegionNum":1,"RegionCategory":"经济学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"BUSINESS, FINANCE","Score":null,"Total":0}
引用次数: 0

摘要

我们从三大平台研究了社交媒体的关注度和情绪:Twitter、StockTwits 和 Seeking Alpha。我们发现,即使在控制了公司信息披露和新闻之后,各平台的关注度仍高度相关,但情绪却并非如此:其第一主成分所能解释的变化比纯粹的特异情绪要少得多。利用市场事件,我们将平台间的差异归因于用户的差异(如专业人士与新手)和平台设计的差异(如帖子的字符限制)。我们还发现,情绪和注意力包含不同的回报相关信息。情感预测了正的次日回报,而关注则预测了负的次日回报。这些结果凸显了同时考虑社交媒体情绪和关注度以及区分不同投资者社交媒体平台的重要性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The social signal

We examine social media attention and sentiment from three major platforms: Twitter, StockTwits, and Seeking Alpha. We find that, even after controlling for firm disclosures and news, attention is highly correlated across platforms, but sentiment is not: its first principal component explains little more variation than purely idiosyncratic sentiment. Using market events, we attribute differences across platforms to differences in users (e.g., professionals versus novices) and differences in platform design (e.g., character limits in posts). We also find that sentiment and attention contain different return-relevant information. Sentiment predicts positive next-day returns, but attention predicts negative next-day returns. These results highlight the importance of considering both social media sentiment and attention, and of distinguishing between different investor social media platforms.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
CiteScore
15.80
自引率
4.50%
发文量
192
审稿时长
37 days
期刊介绍: The Journal of Financial Economics provides a specialized forum for the publication of research in the area of financial economics and the theory of the firm, placing primary emphasis on the highest quality analytical, empirical, and clinical contributions in the following major areas: capital markets, financial institutions, corporate finance, corporate governance, and the economics of organizations.
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术官方微信