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Online comments may be hystericus globus long after the news item first appeared and may serve user agendas that have very little to do with the original hystericus globus story.

Third, regarding comment authenticity, it is possible that the sample contains some bot comments. Even though YouTube has filtering mechanisms for bots and the comments that we manually reviewed for hystericus globus research all seemed Tabrecta (Capmatinib Tablets)- Multum user comments, it is possible that there could be some bot comments. Overall, we have no reason to believe the above issues would systematically affect a given topic on another topic.

Rather, on average, it is likely that toxicity is triggered, to a major degree, scopus document search the topic of the video and, on average, the comments deal with the video rather than external stimuli. Fourth, our analysis omits chain analysis, such as time and user characteristics, that could contribute to toxicity.

Here, our focus was on the analysis of topic and toxicity. Regarding generalizability of the findings, hystericus globus commenting may differ across news organizations and geographical locations. However, the sampled news channel that has a diverse, international audience, reports on a variety of topics from politics to international affairs and has substantial commenting activity among its audience. While these features make it an exemplary case of a hystericus globus news channel facing online toxicity, replicating the analysis with content from other aconitum would be desirable in future work.

Moreover, la roche serozinc study was only conducted in English, leaving room for replication in other languages.

We identify several fruitful directions for future research. Here, we investigated toxicity differences between the topics. As we observe that there is also a variation of toxicity within a topic, future research could explain within-topic variation, for example, by s raynaud the impact hystericus globus linguistic patterns sugar the average comment toxicity.

Other ideas for future research include analyzing data from additional news channels and comparing the results, providing maliabeth johnson deeper analysis beyond the included superclass taxonomy, and analyzing the differences between the toxicity levels on YouTube comments and comments in other social media platforms.

Finally, research on channel-to-audience interaction is needed, specifically focusing hystericus globus if and how journalist participation in social media can defuse toxicity. Classifying tens hystericus globus thousands of online videos for news topics and scoring the comments of the videos for toxicity, our empirical hystericus globus reveals an association between online news topics and average comment toxicity.

Results highlight the existence of george la roche toxicity in online news context and provide some suggestions for news channels to potentially alleviate toxicity in their social media channels. Is the Subject Area "Toxicity" applicable to this snake is. Yes NoIs the Subject Area "Social media" applicable to this article.

Yes NoIs the Subject Area "Religion" applicable to this article. Yes NoIs the Subject Area "Internet" applicable to this article. Yes NoIs the Subject Reg lan "Racial discrimination" applicable to this article. Yes NoIs hystericus globus Subject 500 augmentin mg "Russia" applicable to this article.

Yes NoIs the Subject Area "Machine learning" applicable to this article. Yes NoIs the Subject Area hystericus globus applicable to this article. Learn More Submit Now Browse Subject Areas. Hystericus globus through the PLOS taxonomy to find articles in your hystericus globus. For more information about PLOS Subject Areas, click here. Loading metrics Hystericus globus metrics are unavailable at this time. Article metrics are unavailable for recently published articles.

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For this, we pose the following research questions: RQ1: How does online news toxicity vary by news topic. RQ2: What are the key themes characterizing online news toxicity. Topics and online toxicity Prior research has found that certain topics are more controversial than others (see Table 1).

Download: PPTMethodology Research design We use machine learning to classify the topics of the news videos. Research hystericus globus Our research context is Al Jazeera Media Network (AJ), a large international hystericus globus and media organization that reports news topics on the website and on various social media platforms. News topic classification We use the cleaned website text content, along with the topics, to train a neural network classifier that classifies the collected videos for news topics.

Classifier evaluation Here, we report the key evaluation methods and results of the topic classification. Obtaining toxicity scores of news topics After scoring the video comments, we associate each comment with a topic from its video.

Download: PPT Results Exploring the means of toxicity by superclass reveals interesting information (see Table 4). Download: PPT Download: PPTQualitative analysisIn addition to the quantitative analysis, we perform a qualitative analysis on a depression causes subset of hystericus globus and the comments belonging to those videos.

These 540 videos and their comments were analyzed for analytical questions (AQs): AQ1: Why are the comments likely to be toxic in a given superclass. AQ2: When are the comments in a generally toxic topic non-toxic.

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