Pub Date : 2023-08-08DOI: 10.1080/08838151.2023.2250039
Takayuki Yamatsu, Sang-gil Lee
With the prevalence of connected TV, streaming is replacing linear TV while expanding its functionality. To structurally explain this replacement based on functional similarity, we applied two-way fixed-effects regression to log data from 197,273 smart TVs in Japan from July 2019 to June 2022. Results showed that professional videos on demand primarily substituted linear TV’s recorded viewing, dramas, and movies, whereas substitution by YouTube was broader. Catch-up streaming substituted recorded viewing while complementing viewing without recording. These multiple relationships support the applicability of media substitution theory and foreshadow that functional expansion of streaming would further contribute to linear TV’s replacement.
{"title":"Multiple Relationships between Streaming and Linear TV: Examining Media Substitution Theory Using Big Data","authors":"Takayuki Yamatsu, Sang-gil Lee","doi":"10.1080/08838151.2023.2250039","DOIUrl":"https://doi.org/10.1080/08838151.2023.2250039","url":null,"abstract":"With the prevalence of connected TV, streaming is replacing linear TV while expanding its functionality. To structurally explain this replacement based on functional similarity, we applied two-way fixed-effects regression to log data from 197,273 smart TVs in Japan from July 2019 to June 2022. Results showed that professional videos on demand primarily substituted linear TV’s recorded viewing, dramas, and movies, whereas substitution by YouTube was broader. Catch-up streaming substituted recorded viewing while complementing viewing without recording. These multiple relationships support the applicability of media substitution theory and foreshadow that functional expansion of streaming would further contribute to linear TV’s replacement.","PeriodicalId":48051,"journal":{"name":"Journal of Broadcasting & Electronic Media","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"135840187","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-08-08DOI: 10.1080/08838151.2023.2245937
Sam R. Wilson, B. Quick, Salah H Al-Ghaithi
ABSTRACT We apply a test and extension of Expectancy Violations Theory (EVT) to AT&T’s It Can Wait® promotional messages. Though promising, EVT remains underutilized in mass media contexts. We propose that message elaboration mediates the effects of violating audience expectations of message novelty, dramatic impact, and emotional arousal. Findings indicated that emotional arousal and dramatic impact violations had indirect effects on persuasiveness through message elaboration. This study contributes to theory by providing evidence that in mediated contexts violating message expectations can lead to greater persuasion. Implications for incorporating audience expectations into the design of safety messages are discussed.
本文对AT&T的It Can Wait®促销信息进行了期望违反理论(EVT)的检验和扩展。虽然有希望，但EVT在大众媒体环境中仍未得到充分利用。我们认为，信息阐述介导了违背受众预期的信息新颖性、戏剧性影响和情绪唤醒效应。研究结果表明，情绪唤醒和戏剧性冲击违反通过信息阐述对说服力有间接影响。本研究为理论提供了证据，证明在中介环境中违反信息期望可以导致更大的说服力。讨论了将受众期望纳入安全信息设计的含义。
{"title":"Expectancy Violations, Message Elaboration, and It Can Wait® Messages","authors":"Sam R. Wilson, B. Quick, Salah H Al-Ghaithi","doi":"10.1080/08838151.2023.2245937","DOIUrl":"https://doi.org/10.1080/08838151.2023.2245937","url":null,"abstract":"ABSTRACT We apply a test and extension of Expectancy Violations Theory (EVT) to AT&T’s It Can Wait® promotional messages. Though promising, EVT remains underutilized in mass media contexts. We propose that message elaboration mediates the effects of violating audience expectations of message novelty, dramatic impact, and emotional arousal. Findings indicated that emotional arousal and dramatic impact violations had indirect effects on persuasiveness through message elaboration. This study contributes to theory by providing evidence that in mediated contexts violating message expectations can lead to greater persuasion. Implications for incorporating audience expectations into the design of safety messages are discussed.","PeriodicalId":48051,"journal":{"name":"Journal of Broadcasting & Electronic Media","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-08-08","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47310329","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-23DOI: 10.1080/08838151.2023.2226276
A. Koivula, P. Räsänen, Eetu Marttila, Donna Sedgwick, J. Hawdon
ABSTRACT The article examines media consumption and compliance with health-protective measures during the COVID-19 pandemic. Two-wave, longitudinal surveys were conducted in Finland and the United States in April 2020 and October 2020, with a total of 1,380 participants (N = 1,380). The variables analyzed included daily consumption of different media channels (broadcast, print, and social media), health-protective behavior, and COVID-19 self-efficacy. The results indicated that individuals who consumed more than one media channel on a daily basis exhibited increased health-protective behavior and COVID-19 self-efficacy in both countries. One-sided and social media-based media consumption showed a negative association with health-protective behavior and COVID-19 self-efficacy in both countries. Finally, COVID-19 self-efficacy was found to mediate the relationship between media consumption and health-protective behavior in both countries, with a stronger effect observed in the United States.
{"title":"COVID-19 Compliance and Media Consumption: A Longitudinal Study of Finland and the US During the First Year of COVID-19","authors":"A. Koivula, P. Räsänen, Eetu Marttila, Donna Sedgwick, J. Hawdon","doi":"10.1080/08838151.2023.2226276","DOIUrl":"https://doi.org/10.1080/08838151.2023.2226276","url":null,"abstract":"ABSTRACT The article examines media consumption and compliance with health-protective measures during the COVID-19 pandemic. Two-wave, longitudinal surveys were conducted in Finland and the United States in April 2020 and October 2020, with a total of 1,380 participants (N = 1,380). The variables analyzed included daily consumption of different media channels (broadcast, print, and social media), health-protective behavior, and COVID-19 self-efficacy. The results indicated that individuals who consumed more than one media channel on a daily basis exhibited increased health-protective behavior and COVID-19 self-efficacy in both countries. One-sided and social media-based media consumption showed a negative association with health-protective behavior and COVID-19 self-efficacy in both countries. Finally, COVID-19 self-efficacy was found to mediate the relationship between media consumption and health-protective behavior in both countries, with a stronger effect observed in the United States.","PeriodicalId":48051,"journal":{"name":"Journal of Broadcasting & Electronic Media","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-06-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49509515","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-20DOI: 10.1080/08838151.2023.2226280
Marina Klimenko, Kevin Kapadia, Gaillot Jr Andre
ABSTRACT A content analysis of moral content in the most popular video game franchises with stories between 1996 and 2021 was conducted. The results of the study revealed that there were, on average, 19 moral themes per 3-hour gameplay, and more acts followed basic moral principles. Binding morals (with group loyalty) was the most frequently depicted moral domain; individualizing immoral acts received more negative evaluations. Most moral and immoral acts received no consequences. There was a significant increase in all moral domains from 1996 to 2021. The significance of the findings, as well as limitations and future directions, are discussed
{"title":"What Are the Morals of Video Game Stories? A Content Analysis of the Most Popular Video Games","authors":"Marina Klimenko, Kevin Kapadia, Gaillot Jr Andre","doi":"10.1080/08838151.2023.2226280","DOIUrl":"https://doi.org/10.1080/08838151.2023.2226280","url":null,"abstract":"ABSTRACT A content analysis of moral content in the most popular video game franchises with stories between 1996 and 2021 was conducted. The results of the study revealed that there were, on average, 19 moral themes per 3-hour gameplay, and more acts followed basic moral principles. Binding morals (with group loyalty) was the most frequently depicted moral domain; individualizing immoral acts received more negative evaluations. Most moral and immoral acts received no consequences. There was a significant increase in all moral domains from 1996 to 2021. The significance of the findings, as well as limitations and future directions, are discussed","PeriodicalId":48051,"journal":{"name":"Journal of Broadcasting & Electronic Media","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-06-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48688651","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-19DOI: 10.1080/08838151.2023.2224477
Shuya Pan, Soyoung Jung, Shi Suo
ABSTRACT By applying an extended Technology Acceptance Model (TAM), we specifically examined how TAM-related factors affected two types of usage behaviors of current Metaverse platforms. The use intensity of the popular Metaverses and the adoption of the emerging Metaverses. The study recruited 222 participants through an online survey distributed via Amazon Mechanical Turk (Mturk). The results indicated that the driving forces to use the popular Metaverses were perceived usefulness (PU) and subjective norm (SN), while the adoption of the emerging Metaverses was significantly influenced by perceived enjoyment (PE) and external regulation (ER) of the Covid−19. This research contributes to a deeper understanding of the factors that motivate individuals to engage with contemporary Metaverse platforms, shedding light on the theoretical frameworks of TAM, Diffusion of Innovations Theory (DOI), and Self-determination Theory (SDT). By exploring these dimensions, our study offers a fresh and distinctive perspective on this subject, paving the way for future research in the field.
{"title":"Understanding the Adoption and Usage Behaviors of Popular and Emerging Metaverse Platforms: A Study Based on the Extended Technology Acceptance Model","authors":"Shuya Pan, Soyoung Jung, Shi Suo","doi":"10.1080/08838151.2023.2224477","DOIUrl":"https://doi.org/10.1080/08838151.2023.2224477","url":null,"abstract":"ABSTRACT By applying an extended Technology Acceptance Model (TAM), we specifically examined how TAM-related factors affected two types of usage behaviors of current Metaverse platforms. The use intensity of the popular Metaverses and the adoption of the emerging Metaverses. The study recruited 222 participants through an online survey distributed via Amazon Mechanical Turk (Mturk). The results indicated that the driving forces to use the popular Metaverses were perceived usefulness (PU) and subjective norm (SN), while the adoption of the emerging Metaverses was significantly influenced by perceived enjoyment (PE) and external regulation (ER) of the Covid−19. This research contributes to a deeper understanding of the factors that motivate individuals to engage with contemporary Metaverse platforms, shedding light on the theoretical frameworks of TAM, Diffusion of Innovations Theory (DOI), and Self-determination Theory (SDT). By exploring these dimensions, our study offers a fresh and distinctive perspective on this subject, paving the way for future research in the field.","PeriodicalId":48051,"journal":{"name":"Journal of Broadcasting & Electronic Media","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-06-19","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43700912","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-15DOI: 10.1080/08838151.2023.2224476
Andrew Ventimiglia
{"title":"Platforms and Cultural Production","authors":"Andrew Ventimiglia","doi":"10.1080/08838151.2023.2224476","DOIUrl":"https://doi.org/10.1080/08838151.2023.2224476","url":null,"abstract":"","PeriodicalId":48051,"journal":{"name":"Journal of Broadcasting & Electronic Media","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-06-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47846563","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-06-01DOI: 10.1080/08838151.2023.2218954
Christopher Ali
ABSTRACT This paper develops the concept of “lived policy” for the methodological toolkits of critical, qualitative communication policy scholars. Lived policy seeks to understand how public policies are lived by those impacted by them. It is inspired by research in “lived religion” and “lived theology” which connect theological studies with the lived realities of those who practice religion. Lived policy aims to humanize the policymaking process and the critique of public policy by grounding it in the lives of those most impacted by policy decisions. Examples from a larger study on US rural broadband policy are used to illustrate this approach.
{"title":"Lived Policy: Towards the Humanization of Telecommunications","authors":"Christopher Ali","doi":"10.1080/08838151.2023.2218954","DOIUrl":"https://doi.org/10.1080/08838151.2023.2218954","url":null,"abstract":"ABSTRACT This paper develops the concept of “lived policy” for the methodological toolkits of critical, qualitative communication policy scholars. Lived policy seeks to understand how public policies are lived by those impacted by them. It is inspired by research in “lived religion” and “lived theology” which connect theological studies with the lived realities of those who practice religion. Lived policy aims to humanize the policymaking process and the critique of public policy by grounding it in the lives of those most impacted by policy decisions. Examples from a larger study on US rural broadband policy are used to illustrate this approach.","PeriodicalId":48051,"journal":{"name":"Journal of Broadcasting & Electronic Media","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"47955300","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-27DOI: 10.1080/08838151.2023.2218955
Yang Zhang, Huashan Chen
ABSTRACT Algorithm knowledge of users plays a crucial role in avoiding them from algorithm bias in recommendation systems. Gender of users has been found to correlate with algorithm bias, but also leaving behind a question of whether this relationship can be described by algorithm knowledge. By using Weibo as an example system, we clarify the aforementioned question from a digital divide theory perspective. We combine a traditional method (questionnaire) with a deep learning computational method to explain algorithm bias in two sequential studies. Our findings suggest that algorithm knowledge solely works for men while fails to protect women. Who users follow helps determine what information they are exposed to on Weibo, and this renders female users’ algorithm knowledge useless. This work provides a valuable perspective on algorithm bias: we view algorithm bias as a new digital divide and contribute to the understanding of gender differences by applying the digital divide perspective. Methodologically, we contribute by integrating traditional and computational methods to explain algorithm bias from a folk theory perspective.
{"title":"Can Algorithm Knowledge Stop Women from Being Targeted by Algorithm Bias? The New Digital Divide on Weibo","authors":"Yang Zhang, Huashan Chen","doi":"10.1080/08838151.2023.2218955","DOIUrl":"https://doi.org/10.1080/08838151.2023.2218955","url":null,"abstract":"ABSTRACT Algorithm knowledge of users plays a crucial role in avoiding them from algorithm bias in recommendation systems. Gender of users has been found to correlate with algorithm bias, but also leaving behind a question of whether this relationship can be described by algorithm knowledge. By using Weibo as an example system, we clarify the aforementioned question from a digital divide theory perspective. We combine a traditional method (questionnaire) with a deep learning computational method to explain algorithm bias in two sequential studies. Our findings suggest that algorithm knowledge solely works for men while fails to protect women. Who users follow helps determine what information they are exposed to on Weibo, and this renders female users’ algorithm knowledge useless. This work provides a valuable perspective on algorithm bias: we view algorithm bias as a new digital divide and contribute to the understanding of gender differences by applying the digital divide perspective. Methodologically, we contribute by integrating traditional and computational methods to explain algorithm bias from a folk theory perspective.","PeriodicalId":48051,"journal":{"name":"Journal of Broadcasting & Electronic Media","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46233343","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-27DOI: 10.1080/08838151.2023.2225665
Donghee Shin, Kerk F. Kee
Artificial intelligence (AI) continues to shape the lives of media users today (Wölker & Powell, 2021). Search engines, social media, and other over-thetop service platforms are fueled by data automated and organized through AI and algorithms, which in turn control users and markets. Similarly, the platformization of news and journalism is a growing trend (Dijck et al., 2018). The process of platformization is increasingly facilitating the economic, organizational, and social extensions of digital platforms into online and media ecosystems, fundamentally changing the operations of media industries and journalistic practices. Recently, platformization accelerated due to the drastic breakthroughs in machine learning. Specifically, it is machine learning algorithms that enable different sets of automated processes that transform input data into desired output (Dijck et al., 2018). Algorithms play a key role in curating what information is considered most relevant to users. While popular and effective in practice, these features come with the risk of systematic discrimination, limited transparency, and vague accountability (Moller et al., 2018). While algorithmic filtering may lead to more impartial, thus possibly fairer, processes than those controlled by humans, the process of algorithmic recommendation has been criticized for the tendency to amplify and/or reproduce biases, distort facts, generate information asymmetry, and reinforce process opacity (Ananny & Crawford, 2018). Simply put, algorithmic biases may further compound the algorithmic injustice that machine learning automates and perpetuates. AI-powered platforms have markedly contributed to the rapid diffusion of fake news, mis(dis)information, and deepfakes, which are the detrimental byproducts of platformization (Dan et al., 2021). Misinformation spreads more rapidly and broadly than reliable information does, jeopardizing the credibility of algorithmic journalism. Issues regarding how to safeguard the goals, values, and automated processes of platformization, how to counter fake news, how to discern misinformation, and how to regain media trust in a world of AI remain controversial (Shin, 2023). At the root of these questions are concerns about how to mitigate biases and discriminations in data, JOURNAL OF BROADCASTING & ELECTRONIC MEDIA 2023, VOL. 67, NO. 3, 241–245 https://doi.org/10.1080/08838151.2023.2225665
人工智能（AI）继续塑造着当今媒体用户的生活（Wölker&Powell，2021）。搜索引擎、社交媒体和其他顶级服务平台由人工智能和算法自动化和组织的数据推动，这些数据反过来控制着用户和市场。同样，新闻和新闻学的平台化也是一种日益增长的趋势（Dijck et al.，2018）。平台化进程越来越促进数字平台向在线和媒体生态系统的经济、组织和社会扩展，从根本上改变了媒体行业的运营和新闻实践。最近，由于机器学习的巨大突破，平台化加速了。具体而言，正是机器学习算法实现了将输入数据转换为所需输出的不同自动化过程集（Dijck等人，2018）。算法在管理被认为与用户最相关的信息方面发挥着关键作用。虽然这些特征在实践中流行且有效，但也存在系统性歧视、透明度有限和责任模糊的风险（Moller等人，2018）。虽然算法过滤可能会导致比人类控制的过程更公正，因此可能更公平的过程，但算法推荐过程因倾向于放大和/或复制偏见、扭曲事实、产生信息不对称和强化过程不透明而受到批评（Ananny&Crawford，2018）。简单地说，算法偏见可能会进一步加剧机器学习自动化并使其永久化的算法不公正。人工智能平台显著促进了假新闻、虚假信息和深度伪造的快速传播，这些都是平台化的有害副产品（Dan et al.，2021）。虚假信息比可靠信息传播得更快、更广，危及算法新闻的可信度。关于如何保护平台化的目标、价值观和自动化流程，如何对抗假新闻，如何辨别错误信息，以及如何在人工智能世界中重新获得媒体信任，这些问题仍然存在争议（Shin，2023）。这些问题的根源是对如何减轻数据中的偏见和歧视的担忧，《广播与电子媒体杂志2023》，第67卷，第3期，241-245https://doi.org/10.1080/08838151.2023.2225665
{"title":"Editorial Note for Special Issue on Al and Fake News, Mis(dis)information, and Algorithmic Bias","authors":"Donghee Shin, Kerk F. Kee","doi":"10.1080/08838151.2023.2225665","DOIUrl":"https://doi.org/10.1080/08838151.2023.2225665","url":null,"abstract":"Artificial intelligence (AI) continues to shape the lives of media users today (Wölker & Powell, 2021). Search engines, social media, and other over-thetop service platforms are fueled by data automated and organized through AI and algorithms, which in turn control users and markets. Similarly, the platformization of news and journalism is a growing trend (Dijck et al., 2018). The process of platformization is increasingly facilitating the economic, organizational, and social extensions of digital platforms into online and media ecosystems, fundamentally changing the operations of media industries and journalistic practices. Recently, platformization accelerated due to the drastic breakthroughs in machine learning. Specifically, it is machine learning algorithms that enable different sets of automated processes that transform input data into desired output (Dijck et al., 2018). Algorithms play a key role in curating what information is considered most relevant to users. While popular and effective in practice, these features come with the risk of systematic discrimination, limited transparency, and vague accountability (Moller et al., 2018). While algorithmic filtering may lead to more impartial, thus possibly fairer, processes than those controlled by humans, the process of algorithmic recommendation has been criticized for the tendency to amplify and/or reproduce biases, distort facts, generate information asymmetry, and reinforce process opacity (Ananny & Crawford, 2018). Simply put, algorithmic biases may further compound the algorithmic injustice that machine learning automates and perpetuates. AI-powered platforms have markedly contributed to the rapid diffusion of fake news, mis(dis)information, and deepfakes, which are the detrimental byproducts of platformization (Dan et al., 2021). Misinformation spreads more rapidly and broadly than reliable information does, jeopardizing the credibility of algorithmic journalism. Issues regarding how to safeguard the goals, values, and automated processes of platformization, how to counter fake news, how to discern misinformation, and how to regain media trust in a world of AI remain controversial (Shin, 2023). At the root of these questions are concerns about how to mitigate biases and discriminations in data, JOURNAL OF BROADCASTING & ELECTRONIC MEDIA 2023, VOL. 67, NO. 3, 241–245 https://doi.org/10.1080/08838151.2023.2225665","PeriodicalId":48051,"journal":{"name":"Journal of Broadcasting & Electronic Media","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-05-27","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41353164","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2023-05-04DOI: 10.1080/08838151.2023.2206662
Mengqi Liao
ABSTRACT With the increasing implementation of algorithms across various news platforms, understanding news consumers’ subjective perceptions of algorithmic-based news recommender systems has become critical. A between-subjects experiment (News Recommender System type: content-based filtering vs. collaborative filtering vs. human editorial choice-based recommender system) with 161 participants revealed that participants tended to trust the collaborative filtering system and perceive news recommended by the system to be more credible and less biased compared to editorial choices-based or content-based recommender systems – due to the triggering of the homophily heuristic – even though the three systems recommended the same set of news. Implications were discussed.
{"title":"Understanding the Effects of Personalized Recommender Systems on Political News Perceptions: A Comparison of Content-Based, Collaborative, and Editorial Choice-Based News Recommender System","authors":"Mengqi Liao","doi":"10.1080/08838151.2023.2206662","DOIUrl":"https://doi.org/10.1080/08838151.2023.2206662","url":null,"abstract":"ABSTRACT With the increasing implementation of algorithms across various news platforms, understanding news consumers’ subjective perceptions of algorithmic-based news recommender systems has become critical. A between-subjects experiment (News Recommender System type: content-based filtering vs. collaborative filtering vs. human editorial choice-based recommender system) with 161 participants revealed that participants tended to trust the collaborative filtering system and perceive news recommended by the system to be more credible and less biased compared to editorial choices-based or content-based recommender systems – due to the triggering of the homophily heuristic – even though the three systems recommended the same set of news. Implications were discussed.","PeriodicalId":48051,"journal":{"name":"Journal of Broadcasting & Electronic Media","volume":null,"pages":null},"PeriodicalIF":3.2,"publicationDate":"2023-05-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48097495","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":2,"RegionCategory":"文学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：