Information In Online Communities Research Articles

Account credibility inference based on news-sharing networks

The spread of misinformation poses a threat to the social media ecosystem. Effective countermeasures to mitigate this threat require that social media platforms be able to accurately detect low-credibility accounts even before the content they share can be classified as misinformation. Here we present methods to infer account credibility from information diffusion patterns, in particular leveraging two networks: the reshare network, capturing an account’s trust in other accounts, and the bipartite account-source network, capturing an account’s trust in media sources. We extend network centrality measures and graph embedding techniques, systematically comparing these algorithms on data from diverse contexts and social media platforms. We demonstrate that both kinds of trust networks provide useful signals for estimating account credibility. Some of the proposed methods yield high accuracy, providing promising solutions to promote the dissemination of reliable information in online communities. Two kinds of homophily emerge from our results: accounts tend to have similar credibility if they reshare each other’s content or share content from similar sources. Our methodology invites further investigation into the relationship between accounts and news sources to better characterize misinformation spreaders.

Ethics and the dark side of online communities: mapping the field and a research agenda

AbstractThe rapid growth in the widespread acceptance and usage of the Internet and the ease of creating online communities have brought advantages in terms of swift access to information alongside ethical problems interrelated with the dark side of the workings of these communities. Relevant research approaching ethics and the dark side of online communities has received widespread publication in a diverse set of journals with a wide variety of objectives and readers that has left its academic contribution broadly fragmented. To help shrink this gap in the literature, this study, through undertaking a systematic review, seeks to map the research on ethics and the dark side of online communities to grasp where the literature has come from and where it is going and, consequently, provide opportunities for future research. This study applied a bibliometric approach based on analysis of the bibliographic coupling with the manual coding of documents to examine the literature on the ethics and the dark side of online communities to set out a holistic framework of its different facets. The content and the thematic analysis of 53 studies identified four thematic groups: quality of the information in online communities, virtual identities, safety in online communities, and the content of online communities. The findings of this study also highlight the various shortcomings in the literature on the ethics and dark side of online communities and lead to some research questions that justify future academic research.

A Study on Online Health Community Users' Information Demands Based on the BERT-LDA Model.

As the economy and society develop and the standard of living improves, people's health awareness increases and the demand for health information grows. This study introduces an advanced BERT-LDA model to conduct topic-sentiment analysis within online health communities. It examines nine primary categories of user information requirements: causes, symptoms and manifestations, examination and diagnosis, treatment, self-management and regulation, impact, prevention, social life, and knowledge acquisition. By analyzing the distribution of positive and negative sentiments across each topic, the correlation between various health information demands and emotional expressions is investigated. The model established in this paper integrates BERT's semantic comprehension with LDA's topic modeling capabilities, enhancing the accuracy of topic identification and sentiment analysis while providing a more comprehensive evaluation of user information demands. This research furthers our understanding of users' emotional reactions and presents valuable insights for delivering personalized health information in online communities.

Specifics of online communication of students with the university in social networks and messengers

The article proposes a methodology for analyzing the features of communication between the university and subscribers by the example of considering the communities of P. G. Demidov Yaroslavl State University. The main methods of analysis are: content analysis, event analysis, index analysis and case study. This toolkit made it possible to develop a classification of publications posted in student communities by form and content, to identify the correlation of these characteristics, as well as to determine the most frequently used and interesting format for subscribers to submit information in online communities, to establish the level of subscribers' involvement in the functioning of online platforms. The subject of the study was posts in 3 communities on the Vkontakte social network and in one telegram channel, posted in March-April and July-August 2022. As a result, it is concluded that the telegram channel is the most active in terms of the number of publications, however, it does not contribute to user engagement. The channel is mainly news in nature. In online groups of general orientation, user engagement is lower compared to self-organized activist groups ("Students' Union"and "Students' Trade Union Organization"). Taking into account the specifics of the popularity of certain forms of publications and their contents, as well as the most appropriate time periods for promoting and presenting information, can help in attracting new users and subscribers' interest in the activities of the online community.

Information practices of administrators for controlling information in an online community of new mothers in rural America

AbstractRarely does any empirical investigation show how administrators routinely control information in online communities and alleviate misinformation, hate speech, and information overload supported by profit‐driven algorithms. Thematic analysis of in‐depth phone interviews with members and administrators of a “Vaginal Birth After Cesarean” (VBAC) group with over 500 new mothers on Facebook shows that the administrators make 19 choices for recurring, authoritative but evolving 19 information‐related activities when (a) forming the VBAC group over Facebook for local new mothers, (b) actively recruiting women who had a VBAC or have related competencies, (c) removing doctors and solicitors from the group, (d) setting up and revising guidelines for interactions in the group, (e) maintaining the focus of the group, (f) initiating distinct threads of conversations on the group, (g) tagging experts during conversations in the group, and (h) correcting misinformation. Thirty‐eight information practices of the administrators indicate their nine gatekeeping roles, seven of these roles help administrators alleviate misinformation, hate speech, and information overload. Findings also show that the management of members and their interactions is a prerequisite to controlling information in online communities. Prescriptions to social networking companies and guidelines for administrators of online communities are discussed at the end.

Personalized content recommendation in online health communities

PurposeRecommending suitable content for users of online health communities (OHCs) is critical for overcoming information overload problem and facilitate medical decision making, but remains not fully investigated. This study aims to provide a content recommendation approach to automatically match valuable health-related information for OHC members.Design/methodology/approachA framework of health-related content recommendation was proposed by leveraging rich social information in online communities. The authors constructed user influence relationship (UIR) utilizing users' interaction records, user profiles and user-generated content. The initial user rating matrix and the user post matching matrix were then created by analyzing text content of posts. Finally, the user rating matrix and the recommended content were generated for community members. Datasets were collected from an OHC to evaluate the effectiveness of the proposed approach.FindingsThe experimental results revealed that the proposed method statistically outperformed baseline models in content recommendation for users of OHCs.Research limitations/implicationsThe incorporation of social information can significantly enhance the performance of content recommendation in OHCs. The user post matching degree based on text analysis can improve the effectiveness of recommendation.Practical implicationsThis study potentially contributes to the social support exchange and medical decision making of community members and the sustainable prosperity of OHCs.Originality/valueThis study proposes a novel social content recommendation method for online health consumers based on UIRs by leveraging social information in OHCs. The results indicate the significance of social information in content recommendation of healthcare social media.

How do mothers exchange parenting-related information in online communities? A meta-synthesis

The increase in online social exchange of health information has raised concerns among information and health professionals about the quality and accuracy of the information exchanged. This study investigates how mothers exchange pregnancy- and parenting-related information in online communities. Through a meta-synthesis, we encoded 31 themes and 9 core themes based on the findings from 39 relevant studies, and observed a general pattern of information exchange in mothers' online communities. We found that mothers behave normatively and have a common perception of information values in the community. We also found interactions between mothers' online communities, offline communities, and lifeworld. The study's findings align with the theory of Information Worlds. The current meta-synthesis sheds light on the practice of health care provision and information service and points toward future empirical research.

Translator Professionalism

In recent decades, Translation Studies scholars have highlighted the concept of translator professionalism as a multidimensional term related not only to practitioners' competency in the language domain, but also to their attitudes, behavior, and actions. This article empirically examines how translation clients in Asia perceive translator professionalism. The analysis is based on 72 clients in Asia. The findings suggest that clients perceive the translation occupation as vital to society but have divergent views on whether translation is a profession. They attach importance to translators' proactive behavior at work, such as their reliability. The clients have statistically different opinions on whether or not translators can share their work-related pictures and information in online communities. They also point out that the lack of a certification system affects the professional image of translators. This research allows translators, clients and scholars to have a more informed perception of translator professionalism perceived by Asian clients.

Whose Opinion Matters? Analyzing Relationships Between Bitcoin Prices and User Groups in Online Community

Public interest in cryptocurrencies has consistently risen over the past decade. Owing to this rapid growth, cryptocurrency-related information is being increasingly shared online. As considerable portions of such information in online communities are noise, extracting meaningful information is important. Therefore, judging whose opinion should be considered more important or who the opinion leaders in online communities are is critical. This study analyzed the topics that contain meaningful information, in particular, user groups, by investigating the correlation between topic weights and their price change. The proposed analysis method involves (1) effective classification of the user groups using a hypertext-induced topic selection algorithm, (2) textual information analysis through topic modeling, and (3) the identification of user groups that have a high interest in the Bitcoin price by measuring the correlation between the price and the topics and by measuring the topic similarities between each user group and all users to determine the user group that can effectively represent the entire community. By analyzing the information shared by users, we observed that most users are interested in the price information, whereas users having social influence are not only interested in the price but also in other information.

Consumers’ Social Learning About Videogame Consoles Through Multiple Website Browsing

Abstract This research examines the micro-level correlation between traditional marketing actions (TV ads and public relations) and pre-release consumers’ social learning about videogame consoles (Wii and PS3, launched in 2006). We evaluate consumers’ learning processes via the perusal of information in online communities using “pageview” data for multiple websites from a clickstream panel as indicators. We propose a bivariate Bayesian learning model combined with complementary purchase choices. The proposed model enables simpler estimation of parameters and allows to accommodate detailed information about interactions between social and personal learning processes. From the results, we find empirical evidence that companies’ traditional marketing actions have a greater impact on social learning than on regular personal learning during the pre-launch period. When consumers make purchase decisions, their social beliefs about product quality are weighed at least three times more heavily than their personal beliefs. Counterfactual simulations suggest that by optimizing marketing actions, firms can stimulate consumers’ learning and promote increased product engagement.

Metaliteracy as Pedagogical Framework for Learner-Centered Design in Three MOOC Platforms: Connectivist, Coursera and Canvas

This article examines metaliteracy as a pedagogical model that leverages the assets of MOOC platforms to enhance self-regulated and self-empowered learning. Between 2013 and 2015, a collaborative teaching team within the State University of New York (SUNY) developed three MOOCs on three different platforms—connectivist, Coursera and Canvas—to engage with learners about metaliteracy. As a reframing of information literacy, metaliteracy envisions the learner as an active and metacognitive producer of digital information in online communities and social media environments (Mackey & Jacobson, 2011; 2014). This team of educators, which constitutes the core of the Metaliteracy Learning Collaborative, used metaliteracy as a lens for applied teaching and learning strategies in the development of a cMOOC and two xMOOCs. The metaliteracy MOOCs pushed against the dominant trends of lecture-based, automated MOOC design towards a more learner-centered pedagogy that aligns with key components of metaliteracy.

What Online Networks Offer: Online Network Compositions and Online Learning Experiences of Three Ethnic Groups

This exploratory study examines ethno-cultural diversity in youth´s narratives regarding their online learning experiences while also investigating how these narratives can be understood from the analysis of their online network structure and composition. Based on ego-network data of 79 respondents this study compared the characteristics of the online social networks of native Dutch, Moroccan-Dutch, and Turkish-Dutch youth. Subsequently, thirty interviews were analyzed to compare youth’s narratives regarding two aspects typically associated with 21th century online learning: ‘ individual online exploration’ , and ‘ participation, collaboration and exchange of information in online communities’ . The results show that the three ethnic groups significantly differ regarding their online network composition. Youth’s narratives also reveal that their online learning experiences are ethno-specific. Youth differ regarding the nature of online communities in which they search for information, make new contacts and distribute their own media creations. For example, Turkish-Dutch youth primarily engage in their own ethnic transnational networks to find information and to share media content, whereas Moroccan-Dutch youth seem more open to develop new contacts and to search for information outside of their familiar network. It is suggested that these ethno-specific narratives can be understood as resonating specific network configurations.

A novel method for expert finding in online communities based on concept map and PageRank

AbstractAn online community is a virtual community where people can express their opinions and their knowledge freely. There are a great deal of information in online communities, however there is no way to determine its authenticity. Thus the knowledge which has been shared in online communities is not reliable. By determining expertise level of users and finding experts in online communities the accuracy of posted comments can be evaluated.In this study, a hybrid method for expert finding in online communities is presented which is based on content analysis and social network analysis. The content analysis is based on concept map and the social network analysis is based on PageRank algorithm. To evaluate the proposed method java online community was selected and then correlation between our results and scores prepared by java online community was calculated. Based on obtained results Spearman correlation for 11 subcategories of java online community using this method is 0.904, which is highly an acceptable value.

A Study about the Correlation between Information on Stock Message Boards and Stock Market Activity

Individual investors are increasingly flocking to message boards to seek, clarify, and exchange information. Businesses like Seekingalpha.com and business magazines like Fortune are evaluating, synthesizing, and reporting the comments made on message boards or blogs. In March of 2012, Yahoo! Finance Message Boards recorded 45 million unique visitors per month followed by AOL Money and Finance (19.8 million), and Google Finance (1.6 million) [McIntyre, 2012]. Previous studies in the finance literature suggest that online communities often provide more accurate information than analyst forecasts [Bagnoli et al., 1999; Clarkson et al., 2006]. Some studies empirically show that the volume of posts in online communities have a positive relationship with market activities (e.g., trading volumes) [Antweiler and Frank, 2004; Bagnoli et al., 1999; Das and Chen, 2007; Tumarkin and Whitelaw, 2001]. The findings indicate that information in online communities does impact investors’ investment decisions and trading behaviors. However, research explicating the correlation between information on online communities and stock market activities (e.g., trading volume) is still evolving. Thus, it is important to ask whether a volume of posts on online communities influences trading volumes and whether trading volumes also influence these communities. Online stock message boards offer two different types of information, which can be explained using an economic and a psychological perspective. From a purely economic perspective, one would expect that stock message boards would have a beneficial effect, since they provide timely information at a much lower cost [Bagnoli et al., 1999; Clarkson et al., 2006; Birchler and Butler, 2007]. This indicates that information in stock message boards may provide valuable information investors can use to predict stock market activities and thus may use to make better investment decisions. On the other hand, psychological studies have shown that stock message boards may not necessarily make investors more informed. The related literature argues that confirmation bias causes investors to seek other investors with the same opinions on these stock message boards [Chen and Gu, 2009; Park et al., 2013]. For example, investors may want to share their painful investment experiences with others on stock message boards and are relieved to find they are not alone. In this case, the information on these stock message boards mainly reflects past experience or past information and not valuable and predictable information for market activities. This study thus investigates the two roles of stock message boards–providing valuable information to make future investment decisions or sharing past experiences that reflect mainly investors’ painful or boastful stories. If stock message boards do provide valuable information for stock investment decisions, then investors will use this information and thereby influence stock market activities (e.g., trading volume). On the contrary, if investors made investment decisions and visit stock message boards later, they will mainly share their past experiences with others. In this case, past activities in the stock market will influence the stock message boards. These arguments indicate that there is a correlation between information posted on stock message boards and stock market activities. The previous literature has examined the impact of stock sentiments or the number of posts on stock market activities (e.g., trading volume, volatility, stock prices). However, the studies related to stock sentiments found it difficult to obtain significant results. It is not easy to identify useful information among the millions of posts, many of which can be just noise. As a result, the overall sentiments of stock message boards often carry little information for future stock movements [Das and Chen, 2001; Antweiler and Frank, 2004]. This study notes that as a dependent variable, trading volume is more reliable for capturing the effect of stock message board activities. The finance literature argues that trading volume is an indicator of stock price movements [Das et al., 2005; Das and Chen, 2007]. In this regard, this study investigates the correlation between a number of posts (information on stock message boards) and trading volume (stock market activity). We collected about 100,000 messages of 40 companies at KOSPI (Korea Composite Stock Price Index) from Paxnet, the most popular Korean online stock message board. The messages we collected were divided into in-trading and after-trading hours to examine the correlation between the numbers of posts and trading volumes in detail. Also we collected the volume of the stock of the 40 companies. The vector regression analysis and the granger causality test, 3SLS analysis were performed on our panel data sets. We found that the number of posts on online stock message boards is positively related to prior stock trade volume. Also, we found that the impact of the number of posts on stock trading volumes is not statistically significant. Also, we empirically showed the correlation between stock trading volumes and the number of posts on stock message boards. The results of this study contribute to the IS and finance literature in that we identified online stock message board’s two roles. Also, this study suggests that stock trading managers should carefully monitor information on stock message boards to understand stock market activities in advance.

Credibility of information in online communities

Social media and Web 2.0 empower individuals to generate content online. It is important to better understand the potential added value of social media for e-health service provision. Social support and credibility of health related information generated via social media is a big challenge for online health communities. In this qualitative research, content of discussions from an online health community is analysed. Two themes are examined: online social support and credibility of online forums. Findings show accuracy and credibility of online communities – user profiles, ratings of posts and improved monitoring of content by advisors improve perceived credibility and trust in online forums and communities. Accuracy and perceived credibility of online health communities is pivotal in facilitating social relationships. While consumers are concerned about the credibility of online information, they benefit from social support and are increasingly turning to social media as a source of information and support. Organizations can benefit from better understanding consumer's use of social media, their concerns about information credibility and need for social support.

Do virtual communities matter for the social support of patients?

PurposeThe purpose of this paper is to explore whether online communities meet their potential of providing environments in which social relationships can be readily established to help patients cope with their disease through social support. The paper aims to develop and test a model to examine antecedents of the formation of virtual relationships of cancer patients within virtual communities (VCs) as well as their effects in the form of social assistance.Design/methodology/researchData were collected from members of virtual patient communities in the German‐speaking internet through an online survey to which 301 cancer patients responded. The data were analyzed with partial least square (PLS) structural equation modeling.FindingsVirtual relationships for patients are established in VCs and play an important role in meeting patients' social needs. Important determinants for the formation of virtual relationships within virtual communities for patients are general internet usage intensity (active posting vs lurking) and the perceived disadvantages of CMC. The paper also found that virtual relationships have a strong effect on virtual support of patients; more than 61 per cent of the variance of perceived social assistance of cancer patients was explained by cancer‐related VCs. Emotional support and information exchange delivered through these virtual relationships may help patients to better cope with their illness.Research limitations/implicationsIn contrast to prior research, known determinants for the formation of virtual relationships (i.e. marital status, educational status, gender, and disease‐related factors such as the type of cancer as control variables, as well as general internet usage motives, and perceived advantages of CMC as direct determinants) played a weak role in this study of German cancer patients. Studies on other patient populations (i.e. patients with other acute illnesses in other cultures) are needed to see if results remain consistent.Practical implicationsParticipants and administrators of patient VCs have different design criteria for the improvement of VCs for patients (e.g. concerning community management, personal behaviour and the usage of information in online communities). Once the social mechanisms taking place in online communities are better understood, the systematic redesign of online communities according to the needs of their users should be given priority.Originality/valueLittle research has been conducted examining the role of VCs for social relationships and social networks in general and for patients in particular. Antecedents and effects of virtual social relationships of patients have not been sufficiently theoretically or empirically researched to be better understood. This research combines various determinants and effects of virtual relationships from prior related research. These are integrated into a conceptual model and applied empirically to a new target group, i.e. VCs for patients.