No trade-offs between news and entertainment: Evidence from online engagement data

In today’s high-choice media environment, some scholars are concerned that people selectively consume media content based on personal interests and avoid others, which might lead to audience fragmentation across different content genres. Individually, there might be trade-offs between those genres, especially entertainment versus news. This study analyzed a large user engagement dataset (~40,000 users’ comments) collected from the Chinese information application Toutiao, one of the most popular information distribution platforms in China. The results showed that (1) the commenters were not fragmented between content genres, and (2) the users’ news engagement was positively associated with their entertainment engagement. The findings indicate that the availability of high media choices will not reduce the news engagement of those who have strong interest in entertainment. Instead, news engagement might increase alongside the augmentation of the sum of information engagement. Finally, we discussed the differences between relative news engagement and absolute news engagement.

Repensando la tecnopolítica desde los procesos electorales 2012 y 2018 en México

This article proposes the technopolitical concept as a way to reflect on media changes both in expressions of demand as in processes of social domination and the shaping of public opinion. Longitudinal digital ethnography was carried out on the 2012 and 2018 electoral processes in Mexico. It is concluded that technopolitics is an assembly process where actors interact, with differentiated political objectives, who seek to transform a given historicity or aspire to preserve existing political structures through mobilizations, actions in social media, media content production and other technological appropriations.

When Elon Musk Changes his Tone, Does Bitcoin Adjust Its Tune?

We present a textual analysis that explains how Elon Musk’s sentiments in his Twitter content correlates with price and volatility in the Bitcoin market using the dynamic conditional correlation-generalized autoregressive conditional heteroscedasticity model, allowing less sensitive to window size than traditional models. After examining 10,850 tweets containing 157,378 words posted from December 2017 to May 2021 and rigorously controlling other determinants, we found that the tone of the world’s wealthiest person can drive the Bitcoin market, having a Granger causal relation with returns. In addition, Musk is likely to use positive words in his tweets, and reversal effects exist in the relationship between Bitcoin prices and the optimism presented by Tesla’s CEO. However, we did not find evidence to support linkage between Musk’s sentiments and Bitcoin volatility. Our results are also robust when using a different cryptocurrency, i.e., Ether this paper extends the existing literature about the mechanisms of social media content generated by influential accounts on the Bitcoin market.

Imams’ Prison Service in Nizhny Novgorod Oblast in 2007-2021

This article is devoted to the imams’ prison service of the Spiritual Administration of Muslims of the Nizhny Novgorod Region (DUMNO) in the institutions of the Federal Penitentiary Service of Russia in 2007-2021. The relevance of the study lies in the fact that the imams’ work comes as a contribution to the observance of the convicts’ rights for the freedom of conscience and to the help in practicing their religion. This article describes the evolution of the imams’ prison service as a form of social service in the period from 2007 to 2021 in institutions of to the Offi ce of Federal Penitentiary Service of Russia in Nizhny Novgorod Region. The source base of the study includes materials of the offi cial websites of the DUMNO, the Offi ce of Federal Penitentiary Service of Russia in Nizhny Novgorod Region, the media content, Russian legislation and regulations, interviews with imams, offi cials of Federal Penitentiary Service of Russia and convicts. The study results a vision of the evolution of relations between DUMNO and the Offi ce of Federal Penitentiary Service of Russia in Nizhny Novgorod Region. The paper demonstrates a gradual increase in the number of imams’ contacts, forms of work with convicts to improve the situation in the fi eld of rights of convicts. Moreover, the research exposes the fact of growing numbers of imams having gained experience in prison service. According to the results of the study Islamic education for convicts comes as the important part of imams’ prison service.

PENGARUH MEDIA SOSIAL TIKTOK TERHADAP KEBUTUHAN INFORMASI SEKS EDUKASI PADA GENERASI Z

Sex education is still a topic that is considered taboo in Indonesia, through Tiktok which is a popular application in the world in 2020, it is used as a medium to meet this information need by the @tabu.id account. The purpose of this study was to determine the effect of intensity, media content and attractiveness of using social media on the TikTok @tabu.id account on the fulfillment of sex education information needs. This study uses a quantitative approach with an explanatory survey. The theory used is the Uses Effect Theory. The data collection technique used is a questionnaire or questionnaire and literature study. While the data analysis technique will be collected using a Likert scale. The results of this study are the intensity, message content and attractiveness affect the need for information about sex education. While the magnitude of the influence of sex education information is 6.75%, the magnitude of the influence of infographic messages on sex education information is 33.26% and the magnitude of the influence of sex education information is 15.02%.

Learning Social Media Content Optimization: How Can SMEs Draw the Users' Attention on Official WeChat Accounts?

Application of artificial intelligence is accelerating the digital transformation of enterprises, and digital content optimization is crucial to take the users' attention in social media usage. The purpose of this work is to demonstrate how social media content reaches and impresses more users. Using a sample of 345 articles released by Chinese small and medium-sized enterprises (SMEs) on their official WeChat accounts, we employ the self-determination theory to analyze the effects of content optimization strategies on social media visibility. It is found that articles with enterprise-related information optimized for content related to users' psychological needs (heart-based content optimization, mind-based content optimization, and knowledge-based content optimization) achieved higher visibility than that of sheer enterprise-related information, whereas the enterprise-related information embedded with material incentive (benefits-based content optimization) brings lower visibility. The results confirm the positive effect of psychological needs on the diffusion of enterprise-related information, and provide guidance for SMEs to apply artificial intelligence technology to social media practice.

Post-Symbolic Images in Platform Capitalism

Platform capitalism brings several processes to completion that were already apparent during post-industrial capitalism. One of these involves images and their gradual loss of a symbolic dimension. The mechanisms that platforms employ to direct the production of media content reduce images to objects of immediate use and consumption. Consequently, images fail to synthetise the multiplicity of the social reality: instead of inscribing it within a horizon of meaning, they simply reflect it. This article reconstructs the “de-symbolising” process of images during the various phases of capitalism and explains why a post-symbolic aesthetics should also be viewed as “impolitical”. If the political is indeed symbolic, since the giving of meaning and direction to society (a political task par excellence) also takes place through the construction of symbolic systems, the post-symbolic aesthetic is instead imposed by platforms for purely economic reasons.

A Qualitative Exploration of Social Media Consumption and Use Among Everyday Women Who Participate in CrossFit

Introduction: Social media allows a user to be a content creator and consumer. This paper focuses on the social media engagement of everyday women who participate in CrossFit, exploring differences in how they consume and use social media content. CrossFit women are celebrated for their strength, power, and fitness in the social media community, which is not consistent for all women. Methods: This study used semi-structured focus groups with 47 participants between the ages of 18-54 who were everyday women who participate in CrossFit. The participants self-identified their level of CrossFit as recreational, semi-competitive, competitive, or high-level competitors. Results: Findings reveal two major themes: consuming corporate messaging and using social media for their own benefit, included the subthemes of social support and shifting perceptions. The findings, including supportive quotations from the participants, reveal that these women are critical consumers of social media who express disapproval of traditional media portrayals of women’s bodies. Conclusions: Women’s experiences with CrossFit seem to offer some protection from the negative outcomes associated with consumption of traditional media messaging about women’s bodies.

Transfer Learning with Social Media Content in the Ride-Hailing Domain by Using a Hybrid Machine Learning Architecture

The analysis of the content of posts written on social media has established an important line of research in recent years. The study of these texts, as well as their relationship with each other and their dependence on the platform on which they are written, enables the behavior analysis of users and their opinions with respect to different domains. In this work, a hybrid machine learning-based system has been developed to classify texts using topic modeling techniques and different word-vector representations, as well as traditional text representations. The system has been trained with ride-hailing posts extracted from Reddit, showing promising performance. Then, the generated models have been tested with data extracted from other sources such as Twitter and Google Play, classifying these texts without retraining any models and thus performing Transfer Learning. The obtained results show that our proposed architecture is effective when performing Transfer Learning from data-rich domains and applying them to other sources.

Obesogenic Features of Food-Related Content Aimed at Children on YouTube

Obesity, and particularly childhood obesity, is considered an epidemic by the WHO because of the health problems it causes and its impact on the lives and environment of those who suffer from it. In this article, the term “obesogenic features” refers to the set of supposedly aggravating risk factors that could intensify the proven effect on minors of exposure to food-related media content. The article explores the characteristics of food-related content in YouTube videos aimed at children, with the objective of identifying videos that pose a high risk due to the presence of obesogenic arguments, as well as videos with innovative media trends. It presents an exploratory study of 293 videos (22 hr 41 min) aimed at children and containing food and/or food brands, posted from May 2020 to April 2021 on 28 YouTube channels of food brands and child YouTubers with the largest numbers of subscribers. Child YouTubers often appear to explicitly promote calorie intake as a diet alternative and to disseminate content in which the presence of low-nutrition foods undermines childhood obesity prevention policies. The sensitivity of this target audience and the highly emotional nature of the formats in which messages with obesogenic features appear, such as “challenges,” point to an urgent need to adopt ethical standards and legal measures to regulate such content.