News values on social media: News organizations’ Facebook use

Al-Rawi, Ahmed

doi:10.1177/1464884916636142

Cited by 53 publications

(27 citation statements)

References 43 publications

(40 reference statements)

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Section: Literature Reviewmentioning

confidence: 99%

“…There is a seemingly long history of distributing news content online, especially through websites connected to news organizations (Al‐Rawi, ). In the past, news websites actively invited audiences to interact with content through commenting (Al‐Rawi, ). In fact, 95% of American newspapers with online websites allowed readers to comment in 2011, indicating that comment sections were seen as both popular and profitable (Santana, ).…”

Section: Literature Reviewmentioning

confidence: 99%

“…The popularity of social media has led to their adoption by both individuals and organizations. One prominent organizational use is among news outlets, which use social media to promote and distribute content while simultaneously engaging with audiences (Al‐Rawi, ). This is an especially common practice on Facebook, the world's largest social media site that is the most used in the United States for news consumption (Matsa & Shearer, ).…”

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confidence: 99%

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Hostile media bias on social media: Testing the effect of user comments on perceptions of news bias and credibility

Gearhart

Moe

Zhang

2020

Human Behav and Emerg Tech

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News outlets use social media, especially Facebook, for content distribution and engagement. This exposes consumers to user comments before reading a news article, creating an environment where audiences judge content prior to reading the story. In response to Perloff's (2015) call for research exploring how social media cultivate hostile media effects, this work examines the effects of viewing comments prior to reading a news story on perceptions of bias and credibility. This application tests across issue topics and is not limited to strong partisans or individuals with high issue involvement to test effects on a broader population. Results show comments under Facebook news teasers influence perceptions of bias and credibility. Specifically, those exposed to congruent opinions reported lower perceptions of bias and higher perceptions credibility than exposed to incongruent opinions. Results extend the hostile media bias theory by focusing on all audiences and prescribes practical implications for news practitioners. K E Y W O R D S credibility, Facebook, hostile media bias, online comments The hostile media phenomenon contends that individuals, especially

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Section: Literature Reviewmentioning

confidence: 99%

Section: Literature Reviewmentioning

confidence: 99%

mentioning

confidence: 99%

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Hostile media bias on social media: Testing the effect of user comments on perceptions of news bias and credibility

Gearhart

Moe

Zhang

2020

Human Behav and Emerg Tech

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“…All together has motivated many researchers from Event Detection (ED) field to introduce several ED models [9]. However, several challenges for building high accuracy ED model for Facebook news posts are identified by different researchers [4].…”

Section: Introductionmentioning

confidence: 99%

“…One major example of RED applications is in the identification of real-world events from Facebook news posts. Recently, several RED models for Facebook news posts have been introduced in literature [9]. However, almost all existing models have not provided sufficient summary about the discovered events in terms of answering questions like what has happened, when, where and who was involved [6], [9].…”

Section: Introductionmentioning

confidence: 99%

Event Detection Model for Facebook News Posts

Al-Dyani,

Ahmad*,

Kamaruddin

2019

IJITEE

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Event detection has wide application especially in the area of news streams analyzing where there is a need to monitor what events are emerging and affecting people’s lives. This is crucial for public administrations and policy makers to learn from their previous mistakes to make better decisions in the future. Different researchers have introduced several event detection models for Facebook news posts in. However, majority of these models have not provided adequate information about the discovered news events such as location, people and activity. In addition, existing models have ignored the problem of high dimensional feature space which affects the overall detection performance of the models. This research presents a conceptual event detection model for mining events from large volume of short text Facebook news posts and summarize their valuable information. This is crucial for public administrations and policy makers to learn from their previous mistakes to make better decisions in the future. The proposed model includes pre-processing, feature selection, event detection and summarization phases. The pre-processing phase involves several steps to convert unstructured text news posts into structure data. Feature selection phase to select the optimal feature subset. Meanwhile, event detection phase uses these features to construct undirected weighted graph and apply dynamic graph technique to identify the clusters from the graph and then annotate each cluster to its corresponding event. At the end of this paper, several unresolved problems in the construction of event detection model from Facebook news posts are reported to be used as future work for the current study.

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