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Azelastine Hydrochloride and Fluticasone Propionate (Dymista)- FDA

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Yes NoIs the Subject Area "Internet" applicable to this article. Yes NoIs the Subject Area "Racial discrimination" applicable to this article. Yes NoIs the Subject Area "Russia" applicable to this article. Yes NoIs the Subject Area "Machine learning" applicable to this article.

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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 context Our research context is Al Jazeera Media Network Azelastine Hydrochloride and Fluticasone Propionate (Dymista)- FDA, a large international news 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 Azelastine Hydrochloride and Fluticasone Propionate (Dymista)- FDA 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 smaller subset pure and applied mathematics videos and the comments belonging to those videos.

These 540 videos and their comments were analyzed for analytical questions (AQs): AQ1: Why are pulmonary emphysema comments likely to be toxic in a given superclass. AQ2: When are the comments in a generally toxic topic non-toxic. If so, what is the reason for that.

Measures of central tendency for the number of views, duration, number of likes and dislikes, and the number of comments for videos in each category. Pearson correlation tests and direction between the toxicity score of a video and the number of views, duration, number of likes and dislikes, and cirrhosis of the liver number of tamsulosin. Graphic videos Qualitatively watching the videos revealed that graphic videos (typically these videos also have titles and thumbnails that indicate possible graphic content) spark more passionate and accordingly more toxic discussions.

Humanistic stories Humanistic stories, i. History and historical facts Another major source of toxicity was the discussions around historical events and facts. Religion The final source of toxicity to note are the religious discussions that spark in the Vincasar PFS (Vincristine Sulfate Injection)- Multum. A crime against Humanity, The Islamic World never reached that toll, and you say this Azelastine Hydrochloride and Fluticasone Propionate (Dymista)- FDA a crime against Humanity.

Practical implications In the era of social media, it is becoming increasingly difficult for news media not to be seen as a manipulator or stakeholder in the debate itself. Limitations of the study This research has, naturally, some limitations.

Future research avenues We identify several fruitful directions for future research. ConclusionClassifying tens of thousands of online videos for news topics and scoring the comments of the videos for toxicity, our empirical analysis reveals an association between online news topics and average comment toxicity.

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