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Using an unsupervised machine learning approach, it analyzes 24 million tweets posted by S&P 1500 firms from 2012 to 2020. Results show firms are more likely to share financial information around significantly negative or positive news, such as earnings announcements and the filing of financial statements, with a convex U-shaped pattern that strengthens over time. The symmetric behavior contrasts prior early-sample findings. A Twitter-Latent Dirichlet Allocation model outperforms a dictionary approach for classifying short tweets.",{"@graph":63,"@context":118},[64,80,101],{"@type":65,"itemListElement":66},"BreadcrumbList",[67,71,74,77],{"item":68,"name":69,"@type":70,"position":9},"https://docshare.wps.com","Home","ListItem",{"item":72,"name":10,"@type":70,"position":73},"https://docshare.wps.com/template/",2,{"item":75,"name":31,"@type":70,"position":76},"https://docshare.wps.com/template/social-media/",3,{"item":78,"name":59,"@type":70,"position":79},"https://docshare.wps.com/template/discretionary-dissemination-on-twitter-article-evidence-based-on-24-million-tweets/253862/",4,{"url":78,"name":59,"@type":81,"image":82,"author":87,"headline":59,"publisher":90,"fileFormat":93,"inLanguage":57,"description":61,"dateModified":94,"datePublished":95,"encodingFormat":93,"isAccessibleForFree":96,"interactionStatistic":97},"DigitalDocument",{"url":83,"@type":84,"width":85,"height":86},"https://docshare.wps.com/thumbnails/discretionary-dissemination-on-twitter-article-evidence-based-on-24-million-tweets/253862.png","ImageObject",442,249,{"name":88,"@type":89},"Stanley","Person",{"url":68,"name":91,"@type":92},"DocShare","Organization","application/pdf","2026-10-14","2026-09-13",true,{"@type":98,"interactionType":99,"userInteractionCount":8},"InteractionCounter",{"@type":100},"ViewAction",{"@type":102,"mainEntity":103},"FAQPage",[104,110,114],{"name":105,"@type":106,"acceptedAnswer":107},"What question does the study investigate about Twitter use by firms?","Question",{"text":108,"@type":109},"The study examines whether firms tweet financial information in connection with mandatory accounting events and whether they disseminate extreme good and bad news equally.","Answer",{"name":111,"@type":106,"acceptedAnswer":112},"How are the tweets analyzed in the research?",{"text":113,"@type":109},"An unsupervised machine learning approach is used to analyze 24 million tweets from S&P 1500 firms between 2012 and 2020, and classification is compared across models including Twitter-Latent Dirichlet Allocation.",{"name":115,"@type":106,"acceptedAnswer":116},"What is the main finding about when firms tweet financial information?",{"text":117,"@type":109},"Firms are more likely to post financial tweets around significantly negative or positive news events, producing a convex U-shaped relationship between tweeting likelihood and accounting-event materiality that strengthens over time.","https://schema.org",{"og:url":78,"og:type":120,"og:title":59,"og:site_name":91,"og:description":61},"article",{"robots":122,"canonical":78},"index,follow",{"doc_id":124,"site_id":56},253862,1789973604,{"code":4,"msg":5,"data":127},{"doc_id":124,"user_id":128,"nickname":88,"user_avatar":129,"doc_module":9,"category_id":30,"category_name":31,"doc_title":59,"doc_description":61,"doc_content":130,"file_id":131,"file_url":132,"file_type":133,"file_size":134,"view_count":8,"is_deleted":4,"is_public":9,"is_downloadable":9,"audit_status":9,"page_count":135,"language":136,"language_code":57,"site_id":56,"html_lang":57,"table_of_contents":137,"faqs":138,"seo_title":139,"seo_description":61,"update_tm":140,"read_time":15},2336477405376,"https://ap-avatar.wpscdn.com/davatar_29158cc5080c5b710cf443261637dec0","| Received: 12 December 2018 | Accepted: 4 September 2024 |  |\n| --- | --- | --- |\n| DOI: 10.1111/1911-3846.12986 |  |  |\n| ARTICLE\u003Cbr>| |  |\n| Discretionary dissemination on Twitter\u003Cbr>Richard M. Crowley 1  | Wenli Huang 2 | Hai Lu 3,4 |  |  |\n| 1School of Accountancy, Singapore Management University, Singapore, Singapore 2College of Professional and Continuing Education, Hong Kong Polytechnic University, Hung Hom, Hong Kong 3Rotman School of Management, University of Toronto, Toronto, Ontario, Canada 4Guanghua School of Management, Peking University, Beijing, China\u003Cbr>Correspondence\u003Cbr>Hai Lu, University of Toronto, 105 St. George Street, Toronto, ON M5S 3E6, Canada. [Email:](Email: hai.lu@rotman.utoronto.ca)[ hai.lu@rotman.utoronto.ca](Email: hai.lu@rotman.utoronto.ca) |  | Abstract\u003Cbr>The study provides large-scale descriptive evidence on the timing and nature of corporate financial tweeting. Using an unsupervised machine learning approach to analyze 24 million tweets posted by S&P 1500 firms from 2012 to 2020, we find that firms are more likely to tweet financial information around significantly negative or positive news events, such as earnings announcements and the filing of financial statements. This convex U-shaped relation between the likelihood of posting financial tweets and the materiality of accounting events becomes stronger overtime. Whereas research based on early samples concludes that firms are less likely to disseminate financial information on Twitter when the news is bad and material, the symmetric dissemination behavior we find suggests that these conclusions should be revised. We also show that a machine learning algorithm (Twitter-Latent Dirichlet Allocation) is superior to a dictionary approach in classifying short messages like tweets.\u003Cbr>KEYW ORDS\u003Cbr>disclosures, discretionary dissemination, social media, Twitter\u003Cbr>La diffusion sélective sur Twitter\u003Cbr>Résumé\u003Cbr>Cette étude présente une quantité importante de données descriptives sur la fréquence et le contenu des gazouillis financiers des entreprises. Utilisant une approche d’apprentissage automatique non supervisée, les auteurs analysent 24 millions de gazouillis publiés par les sociétés du S&P 1500 entre 2012 et 2020 . Ils constatent que les entreprises ont tendance à diffuser des informations |\n| Accepted by Eddie Riedl. |  |  |\n| This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.\u003Cbr>© 2024 The Author(s) . Contemporary Accounting Research published by Wiley Periodicals LLC on behalf of Canadian Academic Accounting Association. |  |  |\n\n2454 [wileyonlinelibrary.com/journal/care](wileyonlinelibrary.com/journal/care) Contemp Account Res. 2024;41:2454–2487.  \nDISCRETIONARY DISSEMINATION ON TWITTER  \n2455  \nfinancières lors d’évènements marquants négatifs ou positifs, comme les annonces de résultats ou la publication des états financiers. Cette relation convexe en forme de U entre laprobabilité de publier des gazouillis financiers et l’importance des évènements comptables s’intensifie avec le temps. Alors que les recherches réalisées sur des échantillons initiaux démontrent que les entreprises ont moins tendance à diffuser des informations financières sur Twitter en cas de nouvelles importantes et négatives, le comportement symétrique observé dans cette étudesuggère que ces résultats doivent être réexaminés. De plus, les auteurs démontrent que l’algorithme d’apprentissage automatique (Twitter-LDA) est plus efficace qu’une approche basée sur un dictionnaire pour classifier les minimessages comme les gazouillis.  \nMOT S-CLÉS  \ncommunications d’informations, diffusion sélective, médias sociaux, Twitter  \nJEL CLAS S IFICATION  \nG14, L30, M14, M15, M40  \n1 | INTRODUCTION  \nNews on firm fundamentals is an important information ","cbCainmocOgBVAbR","https://ap.wps.com/l/cbCainmocOgBVAbR","pdf",1485911,34,"English","# Discretionary dissemination on Twitter\n## Abstract\n## Keywords\n## Introduction","[{\"question\":\"What question does the study investigate about Twitter use by firms?\",\"answer\":\"The study examines whether firms tweet financial information in connection with mandatory accounting events and whether they disseminate extreme good and bad news equally.\"},{\"question\":\"How are the tweets analyzed in the research?\",\"answer\":\"An unsupervised machine learning approach is used to analyze 24 million tweets from S\\u0026P 1500 firms between 2012 and 2020, and classification is compared across models including Twitter-Latent Dirichlet Allocation.\"},{\"question\":\"What is the main finding about when firms tweet financial information?\",\"answer\":\"Firms are more likely to post financial tweets around significantly negative or positive news events, producing a convex U-shaped relationship between tweeting likelihood and accounting-event materiality that strengthens over time.\"}]","Discretionary dissemination on Twitter - Article - Evidence based on 24 million tweets | PDF",1789271113]