АНАЛИЗ МЕТОДОВ И ПОДХОДОВ ПРОГНОЗИРОВАНИЯ РАЗВИТИЯ ПРОИСШЕСТВИЙ ПО ИНФОРМАЦИИ ИЗ СОЦИАЛЬНЫХ СЕТЕЙ

This study examines the predictive power of self-disclosed social media information on borrowers’ default in peer-to-peer (P2P) lending and identifies social deterrence as a new underlying mechanism that explains the predictive power. Using a unique data set that combines loan data from a large P2P lending platform with social media presence data from a popular social media site, borrowers’ self-disclosure of their social media account and their social media activities are shown to predict borrowers’ default probability. Leveraging a social media marketing campaign that increases the credibility of the P2P platform and lenders disclosing loan default information on borrowers’ social media accounts as a natural experiment, a difference-in-differences analysis finds a significant decrease in loan default rate and increase in default repayment probability after the event, indicating that borrowers are deterred by potential social stigma. The results suggest that borrowers’ social information can be used not only for credit screening but also for default reduction and debt collection.

Forecasting the U.S. oil markets based on social media information during the COVID-19 pandemic

This study aims to investigate the relationship between social media addiction (in a non-clinical sense) and information literacy (access, evaluation, and use), with a focus on the mediating roles of critical thinking and cognitive flexibility among university students. This study employed a correlational research design. Data were collected from 1,669 university students studying at seven universities in Türkiye, selected using convenience sampling. 1,104 (66.1%) of the sample group are female, while the remaining 565 (33.9%) are male students. Regression-based and bootstrap methods were used to determine the sequential multiple mediation effect of critical thinking and cognitive flexibility between social media addiction and information literacy. The study’s results indicated a moderate negative relationship between social media addiction and information literacy. This suggests that increased social media usage harms levels of information literacy. Furthermore, critical thinking and cognitive flexibility partially mediated this relationship. This emphasises that social media addiction has negative cognitive effects on individuals’ ability to evaluate and process information. The results are consistent with previous studies and highlight the potential adverse effects of excessive social media addiction on critical thinking and cognitive flexibility. The findings indicate that increased social media addiction undermines information literacy by weakening higher-order cognitive processes, and the proposed model explains approximately 39% of the variance.

The massive spread of false information on social media has become a global risk especially in a global pandemic situation like COVID-19. False information detection has thus become a surging research topic in recent months. In recent years, supervised machine learning models have been used to automatically identify false information in social media. However, most of these machine learning models focus only on the language they were trained on. Given the fact that social media platforms are being used in different languages, managing machine learning models for each and every language separately would be chaotic. In this research, we experiment with multilingual models to identify false information in social media by using two recently released multilingual false information detection datasets. We show that multilingual models perform on par with the monolingual models and sometimes even better than the monolingual models to detect false information in social media making them more useful in real-world scenarios.

#InviteMe: Can social media information reduce discrimination? Evidence from a field experiment

A decision model for selecting a suitable supplier is a key to reducing the environmental impact in green supply chain management for high-tech companies. Traditional fuzzy weight average (FWA) adopts linguistic variable to determine weight by experts. However, the weights of FWA have not considered the public voice, meaning the viewpoints of consumers in green supply chain management. This paper focuses on developing a novel decision model for green supplier selection in the One Belt and One Road (OBOR) initiative through a fuzzy weighted average approach with social media. The proposed decision model uses the membership grade of the criteria and sub-criteria and its relative weights, which consider the volume of social media, to establish an analysis matrix of green supplier selection. Then, the proposed fuzzy weighted average approach is considered as an aggregating tool to calculate a synthetic score for each green supplier in the Belt and Road initiative. The final score of the green supplier is ordered by a non-fuzzy performance value ranking method to help the consumer make a decision. A case of green supplier selection in the light-emitting diode (LED) industry is used to demonstrate the proposed decision model. The findings demonstrate (1) the consumer’s main concerns are the “Quality” and “Green products” in LED industry, hence, the ranking of suitable supplier in FWA with social media information model obtained the difference result with tradition FWA; (2) OBOR in the LED industry is not fervently discussed in searches of Google and Twitter; and (3) the FWA with social media information could objectively analyze the green supplier selection because the novel model considers the viewpoints of the consumer.

The perceived credibility of information plays a major role in information selection and influence (Metzger & Flanagin, 2015). Accordingly, past research has examined people's information selection and their decision outcomes, in both web and social media environments (e.g., Knobloch-Westerwick, 2015; Winter & Kramer, 2012). Yet, in spite of this research, the specific processes of people's information selection and credibility assessment are not fully understood. To better specify credibility evaluation behaviors, we employed eye-tracking methods as a means to determine precisely which web page cues (i.e., author, introduction, short advance summary, social media information, pro & con arguments, peer comments, poll on the topic) people attend to as they form opinions about web site credibility. Additionally, we induced participants' information search motivations (i.e., accuracy, defense, impression motivation, or a control). 87 participants in our study viewed a web page for 3.5 minutes while their eye movements were tracked. Think-aloud techniques and post-hoc credibility ratings were used to assess their approaches. Surprisingly, although author information has been shown to have an important impact on both selection and credibility assessment (Winter & Kramer, 2012), results showed that it is consulted last. Primary attention is given to arguments on the web page, and the introduction and short advance summary. Social information appears to be less relevant. Moreover, there is no correlation between duration of browsing various cues and credibility assessment. Also, the patterns of observation are not dependent on information search motivations.

Objectives: The study aimed to examine the relationship between a set of demographic variables and the assessment scale - for undergraduate students at Kuwait University - for information in social media. These variables include gender, age, academic year, devices used to obtain information, and information knowledge. Method: An E-survey was used for the study, a link to the questionnaire was sent to students through the Teams platform, and the usual procedures of reliability were tested on the scale approved. Results: Statistically significant differences were found between some demographic variables and the assessment of information found in social media. Those variables include age, information literacy related to the use of the library and reading culture, in addition to the use of devices related to the internet (laptops, desktops, smartphones, and ipads). No statistically significant differences were found between gender and the evaluation of information in social media. Conclusion: There are demographic factors influencing the ways by which social science students evaluate the information circulated in social media, and these results can be relied upon and benefited from in increasing university students’ awareness of how to evaluate and benefit from the information they obtain from social media.

Social media platforms provide numerous benefits, such as global connectivity and rapid information sharing, but they also pose significant challenges, including managing interactions and assessing content reliability. Many users report feeling overwhelmed by excessive information and uncertainty regarding its accuracy. This study explores three research questions: (i) How does social media utilization influence perceived information disorder experience? (ii) How does social media utilization influence perceived information overload? and (iii) To what extent does perceived information disorder experience mediate the relationship between social media utilization and information overload? Using an online questionnaire, data were collected from Malaysian internet users to measure key constructs. The findings reveal that social media utilization is positively associated with perceived information disorder experience. However, the direct link between social media utilization and information overload was not significant. Importantly, perceived information disorder experience mediates this relationship. These findings have practical implications for social media designers, policymakers, and educators. Designers should address algorithmic biases that prioritize engagement over content accuracy, reducing exposure to disinformation. Policymakers can advocate for stricter content moderation regulations and tools for identifying unreliable information. Educators can enhance media literacy programs, equipping users to critically evaluate information and mitigate the negative effects of information disorder and overload.

The issue of female body anxiety has received widespread attention. However, there are still shortcomings in the exploration of body anxiety caused by metaphorical information in social media in existing research. The article analyzes the methods by which information about regulating women’s body shape is disseminated on social media. Through a detailed exploration of the classification and characteristics of metaphorical information, it is possible to reveal the objective and subjective reasons that trigger female body anxiety on social media and explore the formation mechanism and impact of such metaphorical information. The article concludes that metaphorical information is hidden in social media expressions and difficult to avoid, which exacerbates women’s dissatisfaction with their bodies and promotes the emergence and spread of body anxiety. Based on the above conclusions, the article proposes the following suggestions: reduce exposure to negative information, cultivate critical thinking, and enhance women’s positive cognition of the body through physical and mental coordination. The aforementioned methods can ()effectively cope with body anxiety.

PurposeThe purpose of this paper is to examine whether corporate social media information helps improve analysts’ forecast accuracy.Design/methodology/approachThis study uses hand-collected information on S&P 500 firms’ official Facebook pages and uses posts and reactions to such posts to measure corporate Facebook information. Multivariate regression models are estimated to test the relationship between analysts’ forecast accuracy and corporate Facebook information.FindingsThe results indicate that analysts forecast accuracy is unresponsive to posts. However, analyst forecast errors are decreasing in reactions to posts. These findings are robust to the inclusion of control variables, firm and time fixed effects, and alternative specifications of forecast errors and different pre-forecast time windows.Research limitations/implicationsThis study has some limitations. It focuses only on the S&P 500 firms, which are large and generally provide better information to the market. The sample period coincides with the early period of the corporate Facebook culture. However, more recent data sets are likely to provide stronger results.Practical implicationsThe findings of this study provide support for “information generation” role of social media and show that reactions to corporate Facebook posts are the new and unique information generated from corporate social media activities, which help information intermediaries in improving their forecasting accuracy.Originality/valueThis study makes an important contribution to the literature by separating the information dissemination role of social media from information generation role and establishes the first evidence on how corporate social media information affects forecast accuracy of financial analysts.

To explore how social media affects older adults' subjective well-being (SWB) through underlying mechanisms. Path analysis was performed with 106 Chinese older adults to examine the effects of social media's interactive communication, information acquisition, and leisure and entertainment on SWB via social support, self-efficacy, and depressive symptoms. The model fit well (χ2/df = 5.28, goodness of fit index = 0.86). Social support mediated the positive relationship between interactive communication and SWB, and self-efficacy mediated the positive relationship between information acquisition and SWB. Leisure and entertainment activities on social media showed no significant association with SWB. Social media addresses social support deficits from physical limitations and enhances self-efficacy through information retrieval, thus improving SWB. Findings elucidate how social media influences SWB in older adults, offering theoretical guidance for interventions to enhance their well-being. [Journal of Gerontological Nursing, 51(4), 47-56.].

ABSTRACTSocial media facilitates the formation of identity bubbles that reinforce shared identities, social homophily, and reliance on the information shared within the bubbles. Currently, researchers need more social psychological measures to assess how people perceive their relationships with online networks and information shared on social media. This article reports the development and Finnish and English validations of the identity bubble reinforcement scale (IBRS), consisting of subscales on social identification, homophily, and information bias. Studies 1 and 2 (N = 1200, N = 160; age 15–25 years) validated the 6-item measure (IBRS-6) in Finland and Study 3 replicated the results with both 6-item and 9-item (IBRS-9) measures in the United States (N = 501, age 18–25 years). Across all 3 studies and 2 countries, the IBRS showed good construct validity and correlated positively with social media use and group-behavior measures. The IBRS is an applicable measure for social media group behavior, and its subscales can also be used separately.

Location information in social media is becoming increasingly vital in applications such as election prediction, epidemic forecasting, and emergency detection. However, only a tiny proportion of users proactively share their residence locations (which can be used to approximate the locations of most user-generated content) in their profiles, and inferring the residence location of the remaining users is nontrivial. In this article, the authors propose a framework for residence location inference in social media by jointly considering social, visual, and textual information. They first propose a data-driven approach to explore the use of friendship locality, social proximity, and content proximity for geographically nearby users. Based on these observations, they then propose a location propagation algorithm to effectively infer residence location for social media users. They extensively evaluate the proposed method using a large-scale real dataset and achieve a 15 percent relative improvement over state-of-the-art approaches.

The study aimed to assess the association between adherence to COVID-19 preventive measures and access to media information related to COVID-19. A multicountry, cross-sectional study using an online survey was conducted from June to December 2020. The sample included 1,457 participants from Argentina, Brazil, Chile, and Mexico. The outcome variable was self-reported adherence to preventive measures (handwashing, social distancing, self-isolation, use of face masks, and working from home). The explanatory variable was self-report of following media information related to COVID-19 (watching or reading the news, following social media coverage). Multivariable logistic regression analyses were conducted to determine the associations. Following information on social media was positively associated with higher odds of practicing social distancing [adjusted odds ratio (AOR) = 5.39; 95% confidence interval (CI): 3.93–7.30], self-isolation (AOR = 1.44; 95% CI: 1.08–1.92), use of face masks (AOR = 16.84; 95% CI: 10.03–28.27), handwashing (AOR = 6.95; 95% CI: 4.98–9.71), and working from home (AOR = 1.85; 95% CI: 1.43–2.41). Differences in the use of social media for COVID-19 information were observed among the four countries. Following social media was positively associated with adherence to COVID-19 preventive measures in Latin America. Social media may be used effectively for COVID-19 behavior modification in Latin America.