Jointly Predicting Future Content in Multiple Social Media Sites Based on Multi-task Learning

User-generated contents (UGC) in social media are the direct expression of users’ interests, preferences, and opinions. User behavior prediction based on UGC has increasingly been investigated in recent years. Compared to learning a person’s behavioral patterns in each social media site separately, jointly predicting user behavior in multiple social media sites and complementing each other (cross-site user behavior prediction) can be more accurate. However, cross-site user behavior prediction based on UGC is a challenging task due to the difficulty of cross-site data sampling, the complexity of UGC modeling, and uncertainty of knowledge sharing among different sites. For these problems, we propose a Cross-Site Multi-Task (CSMT) learning method to jointly predict user behavior in multiple social media sites. CSMT mainly derives from the hierarchical attention network and multi-task learning. Using this method, the UGC in each social media site can obtain fine-grained representations in terms of words, topics, posts, hashtags, and time slices as well as the relevances among them, and prediction tasks in different social media sites can be jointly implemented and complement each other. By utilizing two cross-site datasets sampled from Weibo, Douban, Facebook, and Twitter, we validate our method’s superiority on several classification metrics compared with existing related methods.

SIMPA: Statement-to-Item Matching Personality Assessment from text

Automated text-based personality assessment (ATBPA) methods can analyze large amounts of text data and identify nuanced linguistic personality cues. However, current approaches lack the interpretability, explainability, and validity offered by standard questionnaire instruments. To address these weaknesses, we propose an approach that combines questionnaire-based and text-based approaches to personality assessment. Our Statement-to-Item Matching Personality Assessment (SIMPA) framework uses natural language processing methods to detect self-referencing descriptions of personality in a target’s text and utilizes these descriptions for personality assessment. The core of the framework is the notion of a trait-constrained semantic similarity between the target’s freely expressed statements and questionnaire items. The conceptual basis is provided by the realistic accuracy model (RAM), which describes the process of accurate personality judgments and which we extend with a feedback loop mechanism to improve the accuracy of judgments. We present a simple proof-of-concept implementation of SIMPA for ATBPA on the social media site Reddit. We show how the framework can be used directly for unsupervised estimation of a target’s Big 5 scores and indirectly to produce features for a supervised ATBPA model, demonstrating state-of-the-art results for the personality prediction task on Reddit.

Digital Boundaries and Imaginaries of Khasi Ethnic Identity in Social Media

Identity is an integral aspect of human cognition and a composite of varied elements and subjectivities; it is fluidic and contextual. Identity discourses have dominated the socio-cultural and political milieu of Northeast India. A range of scholarship emanating from both within the Northeast region and outside has explored several identity dimensions. As the social media site Facebook allows for the formation of different kinds of interactional groups, this study explored a closed private Facebook group of twenty-five thousand members belonging exclusively to the Khasi ethnic community to understand the phenomenon of ascribing Khasi social identity among members in the online group. The study adopts Tajfel’s Social Identity framework and engages in a netnographic study on an online group. The study’s findings reveal a range of key symbolic manifestations in the co- constructions of Khasi identity in the online space. The study also discovers unique possibilities and affordances proliferated by social media in building collectivities, strengthening ethnic ties, and belongingness in the online space.

How Communicating about Discrimination Influences Attributions of Blame and Condemnation

Across two randomized experiments, we examine how communication about discriminatory acts can influence judgments of blame and condemnation. Specifically, we consider whether attributing discrimination to implicit or explicit bias affects how people evaluate online reports of discrimination. In Study 1 (N = 947), we explore this question in the context of an online news environment, and in Study 2 (N = 121) we replicate our results on a social media site (i.e., Twitter). Across both studies, we document how viewers respond differently to reports of discrimination due to variation in agent motives, the type of bias that purportedly caused the discriminatory behavior, and the extent to which agents are reported to have completed implicit bias training. We discuss our theoretical contribution to perspectives of blame attribution and the communication of bias as well as the practical implications of our findings.

Measuring Profitability From the Use of Personal Data for Targeted Ads

Companies like Facebook and Google track their users’ data to enhance their ads and offer highly targeted ad space. The question is then raised: how much more profitable does collecting data make companies and what is the future of these companies, as rising data privacy concerns are believed to result in the passage of future legislation? In order to isolate the effects of collecting data on profit, the revenue and revenue growth of Google and Facebook were compared to their competitors that do not collect data and revenue was adjusted to find the average per user. Google was compared to another search engine, DuckDuckGo, and Facebook was compared to a social media site, Yubo. Our analysis found that both Google and Facebook earned significantly larger amounts of revenue, per user, than their competitors who do not collect data. However, DuckDuckGo and Yubo both experienced considerably larger revenue growth this past year, highlighting improved success among companies relying on different models for generating revenue. Our research and similar studies will become more important once legislation is passed, as companies may have to pay taxes or fees associated with acquiring users’ data.

“Consent Is F#@king Required”: Hashtag Feminism Surrounding Sexual Consent in a Culture of Postfeminist Contradictions

Hashtag feminism exists in a time of postfeminist contradictions marked by the simultaneous existence of popular feminism and popular misogyny. In one such contradiction, popular feminism has led women to expect the successful negotiation of sexual consent, while popular misogyny permits the circulation of traditional sexual scripts that disregard the necessity of consent. In this study, we analyze messages conveyed through digitized narratives of sexual consent posted on Tumblr, a social media site that is popular among feminist activists, to identify the ways that users construct meaning around the dissonance between expectations for consent and the inequalities that inhibit its negotiation. We specifically explore whether hashtag feminism navigates postfeminist contradictions in a way that simultaneously calls out misogyny and calls on feminism. We find that the Tumblr posts in our sample did both, albeit in a manner that failed to offer tangible solutions to the problem at hand. Calls on feminism were largely limited to tagging feminist allies and recirculating existing feminist campaigns. Thus, we argue that the hashtag ultimately became a handoff to a larger feminist abstraction. Future research should explore conditions under which activists link tangible issues, actors, and agendas to an otherwise abstract popular feminism.

SOCIAL MEDIA AND STUDENTS’ CHOICE OF HIGHER EDUCATION INSTITUTION

Over the past decade, online social networks (OSN) have become ingrained in our daily lives. They have changed the way young people live and become one of the most important means of communication and entertainment. The use of social media by teens and young adults is on the rise. Higher education institutions recognise the value of social media as a tool of communication to provide information to target students and use its platforms to advertise their programmes to prospective students. Students also use Social Media and Facebook to access and analyse information to make informed study decisions. The current study examines how social media in general, and Facebook in particular, influences students' choice of study programme and Higher Education Institute (HEI). Quantitative research methods were employed as being most appropriate for this particular study. A total of 170 students from Oxford Business College (OBC), U.K., participated voluntarily in the survey; sixty-three (63) male and one hundred and seven (107) female students. All students completed a survey questionnaire based on four sections (A, B, C and D) comprising fifteen questions primarily based on the Likert scale. Simple descriptive statistics and SPSS were used to identify and analyse the factors students considered most important (influential) in their (the students’) choice of programme of study and HEI. The most popular social media site was Facebook, followed by Instagram. In regards to influence, Facebook seems to be more influential than other social media sites. It is also obvious that Facebook has been used as a marketing tool by the majority of HEIs. We do not make any claims regarding the generalisability of our study’s findings because of the small sample size and convenience sampling used in the study. However, the results generally support what is already known about the most popular social media site - Facebook - as having a positive influence on students’ choice of programme and Higher Education Institute. <p> </p><p><strong> Article visualizations:</strong></p><p><img src="/-counters-/edu_01/0892/a.php" alt="Hit counter" /></p>

Bullet chats in China: Bilibili, language, and interaction

Bullet chats have grown in popularity in East Asia since 2006, when the Japanese animation website Niconico originated overlaying flying texts on video displays and synchronizing them to the video timeline. This bullet chat function has now gained popularity on Bilibili, a popular Chinese video-sharing social media site with a focus on East Asian pop culture. Bilibili users mix Chinese with foreign languages to create a cyberpidgin vocabulary, adding visual language to express their feelings in a mode that reflects the social norms learned from other East Asian fandoms. Analysis of Bilibili bullet chats provides insight into how social media and online platforms influence user interactions from both linguistic and visual perspectives.

Tumblr’s Xkit Guy, social media modding, and code as resistance

The platformalization of the internet means that fan communities must make homes in spaces that they do not own. Tumblr has lately been the chosen home for many online fandoms because of its affordances for anonymity and lack of censorship. However, the profit motives of Tumblr's owners, especially after Yahoo purchased the site in 2013, are frequently at odds with the affordances that nourish fan communities. Fans on Tumblr are aware of their precarious position, where a few keystrokes by a developer could endanger an affordance that their communities depend on. An examination of the relationship between Tumblr users and Tumblr staff provides a case study of how fan communities push back against platform owners. The Tumblr Xkit Extension, a fan-made browser extension maintained by the volunteer labor of the Xkit Guy, is used to illustrate that the Tumblr community acts as a fandom of a social media site. This lets us understand the Xkit Browser extension as a resistant fan work written in the medium of code. Like video game modding, social media modding is a transformative work that permits fans to oppose the platform's code as law—but one that could also constitute a form of exploited labor.

Intention to Online Shopping on Social Media

high growth of online shopping in Indonesia gave rise to many onlien websites and platforms in Indonesia. Facebook, which is one of the social networks that many people use around the world, is one of the online selling media that is in great demand because it can reach more people. Shopping online on Facebook in addition to providing benefits for sellers and buyers. Online shopping on Facebook requires a high level of trust from buyers regarding the quality of products and serv ices, and ease in obtaining product information and payments because there are no guarantees such as online shop platforms such as shoope, tokopedia, lazada and others which before the goods are received by the customer, then the money from the buyer can not be disbursed. So researchers are interested in researching online shopping interests on the social media site facebook. The results obtained are variable trust, ease of transaction and quality of information positively affect the interest in buying online on facebook.