International Journal of Web Based Communities (9 papers in press)
Moderating effect of gender on the relationship between extraversion, neuroticism, conscientiousness, and Facebook use
by Fethi Calisir, Ecem Basak, Nermin Nergis Yasar
Abstract: This study aims to investigate the moderating effect of gender on the relationship between personality traits such as extraversion, neuroticism, conscientiousness and Facebook usage. A survey methodology was used to gather data and a total of 552 Turkish Facebook users participated in this study. Hierarchical regression analysis was used to test the moderation effect of gender on the relationship between extraversion, neuroticism, conscientiousness and Facebook usage. Our findings suggest that gender moderates the effect of neuroticism on the number of friends and photos, indicating that neurotic male users have more friends and more photos in their Facebook profile than emotionally stable male users. In addition, emotionally stable female users have more friends and more photos in their Facebook profile than neurotic female users. Additionally, neuroticism tends to be a more significant predictor of the number of friends and photos in male users than in females.
Keywords: Extraversion; neuroticism; conscientiousness; gender; Facebook use.
Understanding the Motivation in Massive Open Online Courses: A Twitter Mining Perspective
by Ritanjali Panigrahi
Abstract: Massive open online courses (MOOCs) are attaining recognition world-wide, but their effectiveness in terms of retention is questionable. Several studies have established that motivation is the key to retention in MOOCs. However, a few studies have used social media text analysis to understand the perception of users towards motivation on MOOCs and how MOOC providers engage and motivate their students. This paper uses text mining of motivation related Twitter data on MOOCs to discover the temporal trends, user sentiments, association rules, influencer analysis, and engagement analysis on Twitter. It is found that the users have positive attitudes towards MOOC motivation, and the entities which influence the users are the popular users on Twitter. Furthermore, the MOOC providers engage and motivate the users in the form of motivational quotations, facilitating to ask questions, and sharing experiences. The implications based on the findings are discussed for MOOCs, users, and the government.
Keywords: Massive Open Online Courses; Motivation; Twitter mining; Social media analytics.
A Tag-based Recommender System Framework for Social Bookmarking Websites
by Haibo Liu
Abstract: In social bookmarking websites, social tags contain rich information about individual preference in web resources. Nevertheless, the unsupervised way of tag creation makes the expressions of user's interests are troubled by tag semantic gap. Additionally, in social network sites, the user's interests are influenced by his/her friends' preferences. To handle the problem of personalised interest expression and to recommend the relevant web resource for the users, we propose a tag-based recommender system framework for social bookmarking websites, in which user, tag and resource profiles are expressed reciprocally in a unified form and the 'following interest' is defined based on social network analysis for computing the influence of social relationship on individual interests. We compare our method with several collaborative filtering-based recommendation methods using datasets collected from two social bookmarking websites. The results show that it improves the performance of resource recommendation and outperforms the baseline methods.
Keywords: tag-based recommender system; social bookmarking website; social tag; tag semantic gap; following interest; social network analysis.
Friendship acceptance on Facebook: Men prefer cold calls from attractive women while women favor unattractive friends
by David Weibel, Bartholomäus Wissmath
Abstract: Our study broadens an experiment conducted by Wang et al. (2010). In their study, screenshots of fictitious Facebook profiles were presented to participants of a university class who were then asked whether they would be willing to accept a friendship. In contrast to the original study, we aimed to investigate actual behaviour of social media users instead of mere intentions. Therefore, we sent out actual friendship requests from male or female profile owners who were either attractive or unattractive. The requests were sent to a sample of 800 Facebook users. We could show that about 10% of these users responded to the cold calls. In line with Wang et al. (2010), male users accepted more invitations from attractive female profile owners. However, in contrast to Wang's findings, female users accepted invitations from unattractive profile owners rather than from attractive profile owners, regardless of the profile owners' gender.
Keywords: Facebook; Internet Dating; Internet Gender Issues; Social Networking; Attractiveness; cold calling.
Social Capital: An Influence on Critical to Success Factors in Online Brand Communities
by Stephanie Meek, Claire Lambert, Madeleine Ogilvie, Maria Ryan
Abstract: This study investigates the influence of social capital on the factors that are critical to continued participation in online brand communities (OBCs). The empirical investigation follows a structural equation modelling approach with data from 659 OBC members. Results indicate that social capital as a multidimensional construct represented by shared language, shared vision, social trust and reciprocity has a significant influence on an OBC members' participative behaviour, their sense of belonging (SOB), network ties, perceived enjoyment and perceived ease of use; all of which ensure longevity of the community. Consequently, stakeholders can use this information to develop strategies that will ensure the ongoing success of their OBCs.
Keywords: Online Brand Community; Brand Management; Social Capital; Participative Behaviour; Sense of Belonging; Network Ties; Perceived Enjoyment; Perceived Ease of Use.
We Learn From Each Other: Exploring Interpersonal Communications in Online Communities
by Bo Liang
Abstract: This study investigates the extent to which a participant's prior engagement with other participants predicts the likelihood of this participant's responsiveness to another participant in a later discussion. Further, this study explores the extent to which the content of this participant's reply to another participant demonstrates progress towards advanced learning. This study investigates replies in a diabetes online community using data from ten threads with 431 replies and 209 unique visitors. A mix of qualitative and quantitative methods are used. Results show that a participant, who has more prior engagement with other participants, is more likely to respond to another participant in a later discussion. A participant's reply to another participant contains more content indicating advanced learning. These findings imply that enhancing online community members' interpersonal communications can help transform these members into active social learners, who in turn, benefit the whole community by posting knowledge-based messages.
Keywords: Online communities; social learning; group identity; interpersonal bond; text analysis.
Views versus Subscriptions: Which One Matters to a YouTubers Monetization Success?
by Bo Han
Abstract: The critical factors to a video monetisation success have gained tremendous interests from YouTubers. However, there has not been a rigorous study testing the effects of video view factors and channel subscription factors on a YouTuber's revenues. We introduce a new empirical model to address this knowledge gap. Validating our model by a panel dataset of 116 most viewed YouTuber channels, we find that the new daily views, the daily view growth rate and the existing total views of a YouTuber's videos are significantly positively associated with her daily revenue. The subscription variables do not directly contribute to a YouTuber's daily revenue. Our study is the first of its kind that establishes a clear definition on the term 'YouTubers'. The monetisation model introduced by this study can provide several practical implications to YouTubers and users of other web communities, when they attempt to derive business values from video sharing.
Keywords: YouTube; monetization; YouTuber; video sharing; web community; social media business.
Longlive Friendship? Relationships among friendship, trust and brand loyalty: A study of Starbucks
by Wen-Jung Chang, Yu-Chun Chung, Shu-Hsien Liao
Abstract: Undoubtedly, Facebook has become a rapidly emerging social media during recent decades. It has not only successfully expanded the traditional 'consumer-brand' relationship from the physical channels to the virtual ones, but also shaped complete interaction/communication model between corporate brand and consumers by aggressively build up its brand community. Though Starbucks has already been a well-known brand in Taiwan, few of social media studies has concerned with the influence of friendship and trust on fan's brand loyalty. In view of this, this study based on 340 valid fan samples from Starbuck's fan pages used structural equation modelling (SEM) to validate the research hypotheses. The empirical findings showed that friendship and trust both impact fan's brand loyalty to Starbucks while friendship also influenced trust. Besides, the moderated effect of consumer personality partially existed in our research model.
Keywords: friendship; trust; brand loyalty; consumer personality; Facebook fan page; Starbucks.
Online Social Networking services and Spam Detection Approaches in Opinion Mining- A review
by Meesala Shobha Rani, Sumathy S
Abstract: With the tremendous increase in technological growth and with the diversity of products, online e-commerce servicing sites are becoming competitors for each other to increase their proliferation in business offering to post positive product spam reviews. Users generally express their opinion based on different sentiment orientations, ratings and the features of the product. This tends to create ambiguity at the customers end in arriving at a decision based on the criticism, building fake opinion on the products. A novel framework using meta-heuristic and k-means clustering approach is proposed for identifying opinion spam detection using Flower Pollination, Grey Wolf and Moth Flame. Amazon Automotive product dataset is chosen for analysis and it is observed that Grey Wolf algorithm performs better than Flower Pollination and Moth Flame optimization algorithms in terms of improved convergence speed, mean, standard deviation, variance and elapsed run time.
Keywords: Flower Pollination; Moth-Flame Optimization; Grey-Wolf Optimization; Online Social Networking; Opinion Spam Detection; Opinion Mining; Social Media.