From strangers to friends: Tie formations and online activities in an evolving social network
| Authors | Ameri, Honka, Xie |
| Journal | Journal of Marketing Research |
| Year | 2023 |
| Type | Published Paper |
| Abstract | The authors study how strangers become friends within an evolving online social network. By modeling the coevolution of individual users' friendship tie formations (when and with whom) and their concurrent online activities, the authors uncover important drivers underlying individuals' friendship decisions and, at the same time, quantify the resulting peer effects on individuals' actions. They estimate their model using a novel data set capturing the continuous development of a network and users' entire action histories within the network. The results reveal that similarity (homophily) with a potential friend, the properties of a potential friend's network, and the potential friend's domain expertise all play a role in friendship formation. Via prediction exercises, the authors find that stimulating anime watching is the most effective sitewide intervention, which leads to the highest overall site traffic and the largest number of active users, and that recommending a friend of a friend as a potential friend is the most effective strategy in stimulating friendship tie formation. In contrast to the common finding for static networks, the results indicate that seeding to users with the most friends is not the most effective strategy to increase users' activity levels in an evolving network. |
| URL | https://journals.sagepub.com/doi/abs/10.1177/00222437221107900 |
| Tags | Archival Empirical | Social Network Structure |
Private communication between managers and financial analysts: Evidence from taxi ride patterns in New York City
| Authors | Choy, Hope |
| Year | 2023 |
| Type | Working Paper |
| Abstract | This study constructs a novel measure that aims to capture face-to-face private communications between firm managers and sell-side analysts by mapping detailed, large-volume taxi trip records from New York City to the GPS coordinates of companies and brokerages. Consistent with earnings releases prompting needs for private communications, we observe that daily taxi ride volumes between companies and brokerages increase significantly around earnings announcement dates (EAD) and reach their peak on EAD. After controlling for an extensive set of fixed effects (firm, analyst, year, and firm-broker) and other potential confounding factors, we find that increases in ride volumes around EAD are negatively associated with analysts' earnings forecast errors in periods after EAD and positively associated with the profitability of recommendations issued after EAD (but these effects dissipate over longer horizons). Taken together, our results suggest that analysts may obtain a private source of information orthogonal to their pre-existing information from these in-person meetings, which may help them better understand the implications of current earnings signals for future earnings. |
| Keywords | Private communications, sell-side analysts, taxis, private information, earnings forecasts, stock recommendations, profitability of stock recommendations, earnings announcements, Reg FD |
| URL | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3920680 |
| Tags | Archival Empirical | Asset Pricing, Trading Volume and Market Efficiency | Manager / Firm Behavior | Social Network Structure |
The daily me versus the daily others: How do recommendation algorithms change user interests? Evidence from a knowledge-sharing platform
| Authors | Liu, Cong |
| Journal | Journal of Marketing Research |
| Year | 2023 |
| Type | Published Paper |
| Abstract | Recommender systems on online platforms are often accused of polarizing user attention and consumption. The authors examine this phenomenon using a quasi-experiment conducted by Zhihu, the largest online knowledge-sharing platform (or Q&A community) in China. Zhihu originally used a content-based filtering algorithm, which recommends content to users on the basis of the topics to which each user has subscribed. After more than a year, Zhihu moved to a social filtering algorithm, which recommends content with which users' social connections are already engaged. The authors find that this algorithm change increased the creation of social ties by approximately 15% but decreased question subscriptions by 20% and answer contributions by 23%. The authors show that users' increased social interests mainly involved following popular users, leading to a greater concentration of social interests on the platform. However, users' topical interests became less concentrated, as popular topics received significantly fewer subscribers than unpopular topics. The authors explain these findings by exploring the underlying mechanism. They show that compared with content-based filtering algorithms, social filtering algorithms are more likely to expose general users to content consumed by their followees, who are more interested in niche topics than general users are. |
| URL | https://journals.sagepub.com/doi/abs/10.1177/00222437221134237 |
| Tags | Archival Empirical | Experimental / Survey-Based Empirical | Social Network Structure |
Social media and short sellers
| Authors | Cai, McLean, Zhang, Zhao |
| Year | 2022 |
| Type | Working Paper |
| Abstract | We ask how social media impacts the role of short sellers in financial markets. We find some evidence consistent with manipulation. Prior to high short interest, a stock's social media tone is abnormally positive, but its traditional media tone is not. Once highly shorted, social media tone flips and is abnormally negative. Using the firm-by-firm introduction and temporary suspension of short selling in China as natural experiments, we find that both the volatility of social media tone and the number of posts increase when a firm becomes shortable, and then decrease when shorting was suspended. Highly shorted firms with pump-and-dump social media patterns also have pump-and-dump stock return patterns and abnormally high trading volume. Manipulative social media tone is more likely when there are more posts from active social media users, who are perhaps better able to influence other users. Our findings are consistent with the idea that social networks and social media can enable manipulation. |
| Keywords | Short selling, social media, manipulation, arbitrage |
| URL | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3907480&dgcid=ejournal_htmlemail_capital:markets:market:efficiency:ejournal_abstractlink |
| Tags | Archival Empirical | Asset Pricing, Trading Volume and Market Efficiency | Experimental / Survey-Based Empirical | Media and Textual Analysis | Social Network Structure |
Meet the press: Survey evidence on financial journalists as information intermediaries
| Authors | Call, Emett, Maksymov, Sharp |
| Journal | Journal of Accounting and Economics |
| Year | 2022 |
| Type | Published Paper |
| Abstract | We survey 462 financial journalists and conduct 18 interviews to obtain insights on the inputs to their reporting, the incentives they face, and the factors that influence their coverage decisions. We report many findings relevant to the accounting literature and identify multiple avenues for future research. For example, financial journalists say the likelihood they write about a specific company or CEO increases when the company is controversial or the CEO has a colorful personality, suggesting journalists gravitate toward provocative topics. We also find that financial journalists routinely use company-issued disclosures and private phone calls with company management when developing articles, and that they believe they are evaluated primarily on the accuracy, timeliness, and depth of their articles. Journalists also believe monitoring companies to hold them accountable is one of financial journalism's most important objectives, but they often face negative consequences for writing articles that portray companies in an unfavorable light. |
| Keywords | Business press, financial journalists, media Information, intermediaries, social media, financial analysts |
| URL | https://doi.org/10.1016/j.jacceco.2021.101455 |
| Tags | Archival Empirical | Experimental / Survey-Based Empirical | Manager / Firm Behavior | Media and Textual Analysis | Social Network Structure |
Epidemiological expectations
| Authors | Carroll, Wang |
| Year | 2022 |
| Type | Working Paper | Literature Review Paper |
| Abstract | 'Epidemiological' models of belief formation put social interactions at their core; such models are widely used by scholars who are not economists to study the dynamics of beliefs in populations. We survey the literature in which economists attempting to model the consequences of beliefs about the future -'expectations'- have employed a full-fledged epidemiological approach to explore an economic question. We draw connections to related work on 'contagion,' narrative economics, news/rumor spreading, and the spread of internet memes. A main theme of the paper is that a number of independent developments have recently converged to make epidemiological expectations ('EE') modeling more feasible and appealing than in the past. |
| Keywords | Economic expectations, epidemiological expectations, social interactions, social dynamics, information diffusion, economic narratives |
| URL | https://www.nber.org/papers/w30605?utm_campaign=ntwh&utm_medium=email&utm_source=ntwg4 |
| Tags | Asset Pricing, Trading Volume and Market Efficiency | Consumer Decisions | Financing- and Investment Decisions (Individual) | Investment Decisions (Institutional) | Manager / Firm Behavior | Media and Textual Analysis | Propagation of Noise / Undesirable Outcomes | Social Network Structure | Social Transmission Biases | Theory |
Echo chambers
| Authors | Cookson, Engelberg, Mullins |
| Journal | The Review of Financial Studies |
| Year | 2022 |
| Type | Published Paper |
| Abstract | We find evidence of selective exposure to confirmatory information among 400,000 users on the investor social network StockTwits. Self-described bulls are five times more likely to follow a user with a bullish view of the same stock than are self-described bears. Consequently, bulls see 62 more bullish messages and 24 fewer bearish messages than bears do over the same 50-day period. These âecho chambersâ exist even among professional investors and are strongest for investors who trade on their beliefs. Finally, beliefs formed in echo chambers are associated with lower ex post returns, more siloing of information, and more trading volume. |
| URL | https://academic.oup.com/rfs/article-abstract/36/2/450/6670640 |
| Tags | Archival Empirical | Asset Pricing, Trading Volume and Market Efficiency | Experimental / Survey-Based Empirical | Financing- and Investment Decisions (Individual) | Propagation of Noise / Undesirable Outcomes | Social Network Structure | Social Transmission Biases |
Trust in crowdfunding: Experimental evidence from a fundraising campaign
| Authors | Diep-Nguyen, Yang |
| Year | 2022 |
| Type | Working Paper |
| Abstract | Despite the importance of trust in determining economic outcomes, little is known about what facilitates or hinders interpersonal trust. Using a randomized field experiment of a fundraising campaign, we examine the role of trust and the determinants of perceived trustworthiness in the context of crowdfunding. The key feature of the experiment involves randomized rotations of the campaign design, which differ in the profile photo, details of campaign description, and the update status. The perceived trustworthiness of these rotations is then independently judged by survey participants. We find that while posting updates significantly increases perceived trustworthiness of the campaign and the funds raised, having a more detailed description has little effect. Our follow-up survey reveals that the differential effects are mostly driven by information salience. Interestingly, displaying a white or male profile photo improves the trustworthiness score and generates a higher contribution level, which can be explained by white participants(and donors) and male participants (and donors) preferences. Finally, we find that effects of campaign updates and the profile photo disappear when donors are directly connected to the fundraising team, highlighting the authentication and trust-transmission role of social networks. |
| Keywords | Trust, trustworthiness, crowdfunding, donations |
| URL | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3972418&dgcid=ejournal_htmlemail_behavioral:experimental:economics:ejournal_abstractlink |
| Tags | Experimental / Survey-Based Empirical | Financing- and Investment Decisions (Individual) | Social Network Structure | Theory |
Should retail investors listen to social media analysts? Evidence from text-implied beliefs
| Authors | Dim |
| Year | 2022 |
| Type | Working Paper |
| Abstract | This paper uses machine learning to infer nonprofessional social media investment analysts' (SMAs) beliefs from their opinions on individual stocks. SMAs' average beliefs predict future abnormal returns and earnings surprises. However, there exists substantial heterogeneity in SMAs' ability to form beliefs that yield investment value. Some 13% high-skilled SMAs form beliefs that yield a sizeable one-week three-factor alpha of 61 bps, while the remaining 87% low-skilled SMAs generate only 6 bps. Firm and industry specializations are the most distinctive characteristics of high-skilled SMAs. When forming beliefs, SMAs extrapolate from past returns and herd on the consensus view of their peers. However, these seemingly behavioral biases do not result in systematically wrong beliefs. |
| Keywords | Nonprofessional analysts, belief formation, investor skill, market efficiency, herding, extrapolation, machine learning, natural language processing |
| URL | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=3813252 |
| Tags | Archival Empirical | Asset Pricing, Trading Volume and Market Efficiency | Financing- and Investment Decisions (Individual) | Media and Textual Analysis | Social Network Structure |
Using social network activity data to identify and target job seekers
| Authors | Ebbes, Netzer |
| Journal | Management Science |
| Year | 2022 |
| Type | Published Paper |
| Abstract | An important challenge for many firms is to identify the life transitions of its customers, such as job searching, expecting a child, or purchasing a home. Inferring such transitions, which are generally unobserved to the firm, can offer the firms opportunities to be more relevant to their customers. In this paper, we demonstrate how a social network platform can leverage its longitudinal user data to identify which of its users are likely to be job seekers. Identifying job seekers is at the heart of the business model of professional social network platforms. Our proposed approach builds on the hidden Markov model (HMM) framework to recover the latent state of job search from noisy signals obtained from social network activity data. Specifically, we use the latent states of the HMM to fuse cross-sectional survey responses to a job-seeking status question with longitudinal user activity data, resulting in a partially HMM. Thus, in some time periods, and for some users, we observe a direct measure of the true job-seeking status. We demonstrate that the proposed model can predict not only which users are likely to be job seeking at any point in time but also what activities on the platform are associated with job search and how long the users have been job seeking. Furthermore, we find that targeting job seekers based on our proposed approach can lead to a 29% increase in profits of a targeting campaign relative to the approach that was used by the social network platform. |
| URL | https://pubsonline.informs.org/doi/abs/10.1287/mnsc.2021.3995 |
| Tags | Archival Empirical | Experimental / Survey-Based Empirical | Manager / Firm Behavior | Social Network Structure |
The democratization of investment research and the informativeness of retail investor trading
| Authors | Farrell, Green, Jame, Markov |
| Journal | Journal of Financial Economics |
| Year | 2022 |
| Type | Published Paper |
| Abstract | We study the effects of social media on the informativeness of retail trading. Our identification strategy exploits the editorial delay between report submission and publication on Seeking Alpha, a popular crowdsourced investment research platform. We find the ability of retail order imbalances to predict the cross-section of stock returns and cash-flow news increases sharply in the intraday post-publication window relative to the pre-publication window. The findings are robust to controlling for report tone and stronger for reports authored by more capable contributors. The evidence suggests that recent technology-enabled innovations in how individuals share information help retail investors become better informed. |
| Keywords | Investment research, Seeking alpha, retail investors, informed trading |
| URL | https://www.sciencedirect.com/science/article/abs/pii/S0304405X21004050 |
| Tags | Archival Empirical | Asset Pricing, Trading Volume and Market Efficiency | Financing- and Investment Decisions (Individual) | Social Network Structure |
Labor reactions to credit deterioration: Evidence from LinkedIn activity
| Authors | Gortmaker, Jeffers, Lee |
| Year | 2022 |
| Type | Working Paper |
| Abstract | We analyze worker reactions to firms' credit deterioration. Using weekly anonymized networking activity on LinkedIn, we show workers initiate more connections immediately following a negative credit event, even at firms far from bankruptcy. Our results suggest that workers are driven by concerns about both unemployment and future prospects at their firm. Heightened networking activity is associated with contemporaneous and future departures, especially at highly-rated firms. Other negative events like missed earnings and equity sell recommendations do not trigger similar reactions. Overall, our results indicate that the latent build-up of connections triggered by credit deterioration represents a source of fragility for firms. |
| Keywords | Network formation, credit deterioration, labor & finance, financial distress, labor fragility |
| URL | https://papers.ssrn.com/sol3/Papers.cfm?abstract_id=3456285 |
| Tags | Archival Empirical | Media and Textual Analysis | Social Network Structure |
Competing for talent: Firms, managers, and social networks
| Authors | Hacamo, Kleiner |
| Journal | The Review of Financial Studies |
| Year | 2022 |
| Type | Published Paper |
| Abstract | Do social networks help firms recruit talented managers? In our setting, firms are randomly connected to prospective young managers through former employees. Under a discrete choice model, we find networks increase the likelihood firms hire high-ability managers, while having no effect on the hiring rate of low-ability managers. Effects are greatest for nonlocal firms, strong ties, and peers living in the same neighborhood. Survey evidence suggests social networks promote recruitment by providing information about firm fundamentals to potential applicants. Our results help rationalize why the majority of managers hold prior connections to the firm. |
| URL | https://academic.oup.com/rfs/article-abstract/35/1/207/6146360?redirectedFrom=fulltext |
| Tags | Archival Empirical | Manager / Firm Behavior | Social Network Structure |
Word-of-mouth communication and financial decision making
| Authors | Hwang |
| Year | 2022 |
| Type | Working Paper | Literature Review Paper |
| Abstract | I review the empirical literature on word of mouth (WOM) among investors. I begin with an outline of the empirical challenges that WOM research faces and possible strategies to overcome those challenges. I then discuss recent studies on WOM among retail and institutional investors. The research to date provides compelling evidence that WOM importantly determines investment decisions. On balance, the information transmitted through WOM does not appear to help investors make better investment decisions. I explore possible reasons. I also discuss potential asset pricing implications, the emergence of social technologies, and possible avenues for future research. |
| Keywords | Social asset pricing, social finance, investor psychology, investor behavior, asset prices |
| URL | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4118285 |
| Tags | Asset Pricing, Trading Volume and Market Efficiency | Financing- and Investment Decisions (Individual) | Investment Decisions (Institutional) | Propagation of Noise / Undesirable Outcomes | Social Network Structure | Social Transmission Biases |
Social proximity to capital: Implications for investors and firms
| Authors | Kuchler, Li, Peng, Stroebel, Zhou |
| Journal | The Review of Financial Studies |
| Year | 2022 |
| Type | Published Paper |
| Abstract | We show that institutional investors are more likely to invest in firms from regions to which they have stronger social ties but find no evidence that these investments earn a differential return. Firms in regions with stronger social ties to locations with many institutional investors have higher valuations and liquidity. These effects are largest for small firms with little analyst coverage, suggesting that the investors' behavior is explained by their increased awareness of firms in socially proximate locations. Our results highlight that the social structure of regions affects firms' access to capital and contributes to geographic differences in economic outcomes. |
| URL | https://academic.oup.com/rfs/article-abstract/35/6/2743/6372708?redirectedFrom=fulltext |
| Tags | Archival Empirical | Investment Decisions (Institutional) | Social Network Structure |
Social learning and analyst behavior
| Authors | Kumar, Rantala, Xu |
| Journal | Journal of Financial Economics |
| Year | 2022 |
| Type | Published Paper |
| Abstract | This study examines whether sell-side equity analysts engage in "social learning" in which their earnings forecasts for certain firms are influenced by the forecasts and outcomes of "peer" analysts associated with other firms in their respective portfolios. We find that analyst optimism is negatively correlated with recent forecast errors, by peers, on other firms in the analyst's portfolio. An analyst is also more likely to issue "bold" forecasts when peers recently issued similar forecasts for other portfolio firms. Analysts learn more from peers with similar personal characteristics. Overall, social learning benefits analysts and improves their forecast accuracy. |
| Keywords | Sell-side equity analysts, social learning, bold forecasts, forecast accuracy |
| URL | https://doi.org/10.1016/j.jfineco.2021.06.011 |
| Tags | Archival Empirical | Asset Pricing, Trading Volume and Market Efficiency | Productivity Spillovers | Social Network Structure |
Social Networks, trading, and liquidity
| Authors | Peng, Wang, Zhou |
| Year | 2022 |
| Type | Working Paper | Literature Review Paper |
| Abstract | The recent meme stock saga has drawn attention to the growing role of social networks in capital markets. In this paper, the authors summarize the latest research that uses large scale, representative, real-world social network data to study social networks' influences on trading, liquidity, and valuations of stocks. Institutional investors invest more heavily in stocks if there are strong social ties between the geographic locations of the institution's headquarters and the firm's headquarters. Further, a firm's social ties to large institutional investors reduce its cost of capital, increase its valuation, and strengthen its liquidity. Social networks help to timely disseminate important news releases into prices, but also trigger belief divergence and generate persistent excess trading. Moreover, social interactions can amplify investors' behavioral biases and contribute to retail investors' attraction to lottery-type stocks. The authors provide additional examples to further illustrate why the roles of social networks are of particular importance to market participants. |
| Keywords | Social networks, market liquidity |
| URL | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4099114 |
| Tags | Asset Pricing, Trading Volume and Market Efficiency | Financing- and Investment Decisions (Individual) | Investment Decisions (Institutional) | Manager / Firm Behavior | Propagation of Noise / Undesirable Outcomes | Social Network Structure | Theory |
Social Networks, trading, and liquidity
| Authors | Peng, Wang, Zhou |
| Year | 2022 |
| Type | Working Paper | Literature Review Paper |
| Abstract | The recent meme stock saga has drawn attention to the growing role of social networks in capital markets. In this paper, the authors summarize the latest research that uses large scale, representative, real-world social network data to study social networks' influences on trading, liquidity, and valuations of stocks. Institutional investors invest more heavily in stocks if there are strong social ties between the geographic locations of the institution's headquarters and the firm's headquarters. Further, a firm's social ties to large institutional investors reduce its cost of capital, increase its valuation, and strengthen its liquidity. Social networks help to timely disseminate important news releases into prices, but also trigger belief divergence and generate persistent excess trading. Moreover, social interactions can amplify investors' behavioral biases and contribute to retail investors' attraction to lottery-type stocks. The authors provide additional examples to further illustrate why the roles of social networks are of particular importance to market participants. |
| Keywords | social networks, market liquidity |
| URL | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4099114 |
| Tags | Asset Pricing, Trading Volume and Market Efficiency | Financing- and Investment Decisions (Individual) | Investment Decisions (Institutional) | Manager / Firm Behavior | Propagation of Noise / Undesirable Outcomes | Social Network Structure | Theory |
Influencers, inefficiency and fraud - The Bitcoin price discovery network under the microscope
| Authors | Trimborn, Chen, Chen |
| Year | 2022 |
| Type | Working Paper |
| Abstract | We present a TriSNAR modeling framework for understanding the dynamic interactions of multiple markets for Bitcoin trading, including market efficiency, and for identifying influential exchanges in the global trading network. We are particularly interested in identifying exchanges that are market leaders. Out of 339 weeks (6.5 years of data), we identify 104 weeks in which TriSNAR provides the best MSFE out of 6 contestants and significantly outperforms all other models. Among 194 Bitcoin exchanges, we find that exchange Kraken was the leading exchange prior to the market frenzy of 2017, in particular in 2016. In addition, price discovery shows that the Bitcoin exchange networks efficiency decreased from 2015 to 2017, and increased since 2018. We analyse the relation between blockchain fund flows and influential exchanges, and observe that wealthy holders of Bitcoin transact funds to exchanges when influential exchanges arise. We investigate the finite sample and asymptotic properties of TriSNAR. Compared to alternative methods, TriSNAR outperforms in terms of accuracy and ability to discover multi-market network structures. |
| Keywords | Influencer identification, blockchain network analysis, market efficiency, structure detection, bitcoin exchanges |
| URL | https://papers.ssrn.com/sol3/papers.cfm?abstract_id=4071212 |
| Tags | Asset Pricing, Trading Volume and Market Efficiency | Social Network Structure | Theory |
Entrepreneurial spillovers across coworkers
| Authors | Wallskog |
| Journal | Review of Financial Studies |
| Year | 2022 |
| Type | Published Paper |
| Abstract | Using large-scale administrative data, I track the employment and entrepreneurship of over forty million Americans and investigate entrepreneurial spillovers across coworkers, based on the idea that individuals who start their own firms learn institutional knowledge and entrepreneurial skills that they may teach others. I find that an individual whose current coworkers have more prior entrepreneurship experience is more likely to become an entrepreneur themself within the next five years, and these spillovers are strongest among workers with similar jobs and demographics. Furthermore, an individual is more likely to become a successful entrepreneur if those coworkers were themselves successful entrepreneurs. To quantify the role of these spillovers, I build a structural model of entrepreneurship and learning and estimate that the aggregate entrepreneurship rate would be 10% lower in the absence of learning. |
| Keywords | Spillovers, peer effect, entrepreneurship, social learning |
| URL | https://melaniewallskog.github.io/files/wallskog_jmp.pdf |
| Tags | Archival Empirical | Experimental / Survey-Based Empirical | Productivity Spillovers | Social Network Structure |