{"title":"Strategic Content Generation and Monetization in Financial Social Media","authors":"Ding Li, Khim-Yong Goh, Cheng-Suang Heng","doi":"10.1287/isre.2022.0482","DOIUrl":null,"url":null,"abstract":"Strategic Content Generation and Monetization in Financial Social MediaAbstractFinancial social media, which relies on social media analysts (SMAs) to contribute content to investors, is a crucial channel for investors to gain financial information and for SMAs to monetize their content. The interactive nature of financial social media has given SMAs the opportunity to gain access to the investor preferences of their own audience base for financial content. Our study documents that SMAs would exploit this opportunity to strategically generate and monetize content by catering to investor preferences. Specifically, SMAs would increase the (negative) sentiment of the content if paid subscribers’ preferences for (negative) sentiment grow. Additionally, an SMA is more likely to produce paid content when the expected free readership increases and is less likely to do so when the expected paid subscriptions increase. Our findings suggest that the sentiment of financial social media content is not a mere reflection or prediction of stock market movements but also a result of SMAs’ reaction to investor preferences. We thus illustrate an approach to identify the SMAs who may amplify the investors’ confirmation biases because of such catering behaviors so that platform managers and regulators alike can utilize this method to improve the content quality of financial social media.","PeriodicalId":48411,"journal":{"name":"Information Systems Research","volume":"48 1","pages":""},"PeriodicalIF":5.0000,"publicationDate":"2024-02-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Information Systems Research","FirstCategoryId":"91","ListUrlMain":"https://doi.org/10.1287/isre.2022.0482","RegionNum":3,"RegionCategory":"管理学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"INFORMATION SCIENCE & LIBRARY SCIENCE","Score":null,"Total":0}
引用次数: 0
Abstract
Strategic Content Generation and Monetization in Financial Social MediaAbstractFinancial social media, which relies on social media analysts (SMAs) to contribute content to investors, is a crucial channel for investors to gain financial information and for SMAs to monetize their content. The interactive nature of financial social media has given SMAs the opportunity to gain access to the investor preferences of their own audience base for financial content. Our study documents that SMAs would exploit this opportunity to strategically generate and monetize content by catering to investor preferences. Specifically, SMAs would increase the (negative) sentiment of the content if paid subscribers’ preferences for (negative) sentiment grow. Additionally, an SMA is more likely to produce paid content when the expected free readership increases and is less likely to do so when the expected paid subscriptions increase. Our findings suggest that the sentiment of financial social media content is not a mere reflection or prediction of stock market movements but also a result of SMAs’ reaction to investor preferences. We thus illustrate an approach to identify the SMAs who may amplify the investors’ confirmation biases because of such catering behaviors so that platform managers and regulators alike can utilize this method to improve the content quality of financial social media.
金融社交媒体中的战略性内容生成和货币化摘要金融社交媒体依靠社交媒体分析师(SMA)为投资者提供内容,是投资者获取金融信息和 SMA 实现内容货币化的重要渠道。金融社交媒体的互动性使 SMA 有机会了解其受众群体中投资者对金融内容的偏好。我们的研究表明,SMA 将利用这一机会,通过迎合投资者的偏好,战略性地生成内容并实现内容货币化。具体来说,如果付费用户对(负面)情绪的偏好增加,SMA 就会增加内容的(负面)情绪。此外,当预期免费读者人数增加时,SMA 更有可能制作付费内容,而当预期付费订阅人数增加时,SMA 则不太可能制作付费内容。我们的研究结果表明,金融社交媒体内容的情绪不仅仅是对股市走势的反映或预测,也是 SMA 对投资者偏好做出反应的结果。因此,我们说明了一种方法,可以识别出因这种迎合行为而可能放大投资者确认偏差的 SMA,从而使平台管理者和监管者都能利用这种方法来提高金融社交媒体的内容质量。
期刊介绍:
ISR (Information Systems Research) is a journal of INFORMS, the Institute for Operations Research and the Management Sciences. Information Systems Research is a leading international journal of theory, research, and intellectual development, focused on information systems in organizations, institutions, the economy, and society.