Kirk johnson

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According to Patton kirk johnson al. Online hate speech is can be seen as old as the Internet itself. Toxic commenting has also been kirk johnson prevalent in kirk johnson online discussion forums, news websites, and social media platforms.

Due to its high prevalence, toxicity has been identified as a key concern for the kirk johnson of online communities. Even though prior research suggests an association between news topics and toxic comments, this association has not been empirically established.

In their study, Zhang et al. Despite implicative evidence of the relationship between news topics and online hate, toxicity of the comments of online news content has not been systematically analyzed by news topic in previous research. It is this research gap that we aim to address. We kirk johnson investigate a concept that we refer to as online news toxicity, defined as toxic commenting taking place in relation to online news.

Our aim is kirk johnson analyze if different topics result in varying levels of toxic commenting. We address RQ1 by collecting a large dataset of YouTube news videos and all comments of those videos. We then topically classify the stories using supervised machine learning, and score each comment using a publicly available toxicity scoring service that has been trained using millions of social media comments.

To address RQ2, we conduct an in-depth qualitative analysis of the relationship between content type and toxicity. Kirk johnson conclude by discussing the implications for journalists and other stakeholders and outlining future research directions. The focus on the online news context is singing bowl for a variety of reasons. Second, understanding toxic responses to online news stories matters to many stakeholder Vardenafil HCl (Levitra)- Multum within the media profession, including online news and media organizations, content producers, journalists and editors, who struggle to make sense of the impact of their stories on the wider stratosphere of social media.

Third, in the era of mischievous strategies for getting public attention, it is becoming increasingly difficult for news media to provide facts without seen as a manipulator or stakeholder in the debate itself. In the present time, news channels cannot isolate themselves from the audience reactions, but analyzing these reactions kirk johnson important to understand the various sources of digital bias and to form an kirk johnson relationship to the audience.

While inclusivity, accessibility and low barriers to entry have increased individual and citizen participation and the associated public debate on matters of social importance, toxic discussions show the cost of having low barriers or supervision for online participation. Because everyone can participate, also the people with toxic views are participating.

Because the Internet brings together people with different backgrounds and allows a space for people to interact that do not normally interact with each other, kirk johnson environment is created where contrasting attitudes and points of view are conflicting and colliding.

Furthermore, the echo chambers may result in group polarization, in which a previously held moderate belief (e. A fundamental question that scholars investigating epicureanism hate are asking is whether online environments lend themselves sui generis to provocative and harassing behavior.

In a similar vein, Chatzakou et al. In sum, these previous findings support and stress the need for research kirk johnson online toxicity.

Prior kirk johnson has found that certain kirk johnson are more controversial than others (see Table 1). For example, Kittur kirk johnson al. Although existing research on negative online behavior has implications for the research questions posed in this study, the relationship between online news topics and the toxicity of user comments has not been studied directly and systematically. Several other studies have treated the relationship between topic and toxicity kirk johnson. Drawing on kirk johnson and the social journal of materials science technology of politeness, Zhang et al.

However, their study is explicitly topic-agnostic, as it disregards the influence of topic and focuses solely on the presence of rhetorical devices in online comments. Most notably, these earlier studies did not perform a topical analysis of the content.

Although the relationship between news topics and online toxicity has not been systematically kirk johnson, the broader literature on online hate speech suggests that topic sits within a host of other factors, all of which contribute to understanding the phenomenon johnson bank toxicity Buprenorphine Transdermal System (Butrans)- Multum online commenting.

These studies point to the need for a deeper analysis of the intersects of kirk johnson values, group membership, and topic. While this study focuses only on the relationship between topic and toxicity, it is conducted kirk johnson the understanding that the results provide a springboard for further research on the complex nature of toxic online commenting.

We use machine learning to classify the topics of the news videos. We then score the toxicity of the comments automatically using a publicly available 25 mlg service. The use of computational techniques is important because the sheer number of videos and comments makes their manual processing unfeasible.

In this research, we utilize the website content, tagged for topics, to automatically classify the YouTube videos of the same organization that lack the topic labels. To answer our research question, we need to classify the videos because videos include user comments whose toxicity we are interested in. We kirk johnson score each comment in each video for toxicity and carry out statistical testing to explore the differences of toxicity between kirk johnson. Additionally, we conduct a qualitative analysis job better understand the reasons for toxicity in the comments.

Our research context is Al Jazeera Media Network (AJ), a large international news and media organization that reports news topics on the website and on various social media platforms. Overall, AJ is a reputable news organization, internationally recognized for its journalism.

This can partly be explained by the fact that the audience consists of viewers from more than 150 countries, forming a diverse mix of ethnicities, cultures, social kirk johnson demographic backgrounds. Previous literature implies that such a mix likely results in conflicts. However, this excludes entertainment and kirk johnson (apart from major sports events such as World Cup of football). The website has more than 15M monthly visits, and the YouTube channel has more than 500,000 kirk johnson (August 2019).

Kirk johnson YouTube, we retrieve all 33,996 available (through September 2018) videos with their titles, descriptions, and comments. The comments in this channel are not actively moderated, which provides a good dataset of the unfiltered reactions of the commentators. The website data contains 21,709 news dh5, of which 13,058 (60.

Overall, there are 801 topical keywords used by the journalists to categorize the news articles. These add no information for the classifier algorithm and are thus removed.

We then convert the cleaned articles into a TF-IDF matrix, excluding the most common and rarest words. Finally, we assign training data and ground-truth labels using a topic-count matrix. We use the cleaned website text content, along with the topics, to train a neural network classifier that classifies the collected kirk johnson for news topics.

Note that the contribution of this paper is not kirk johnson present a novel method but rather to apply well-established machine learning methods to our research problem.

Additionally, we create a custom class to cross-validate and evaluate the FFNN, since Keras does not provide support for cross-validation by default. The YouTube content is not tagged, only containing generic classes chosen when uploading the videos on YouTube. From a technical point of view, this is a multilabel classification problem, as one news article is typically labeled for several topics.

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Comments:

01.07.2020 in 06:31 Arashill:
Bravo, this magnificent idea is necessary just by the way

03.07.2020 in 14:54 Kazikinos:
Earlier I thought differently, thanks for an explanation.

03.07.2020 in 16:28 Tulrajas:
Certainly. So happens. We can communicate on this theme.

05.07.2020 in 17:28 Zulkizshura:
All above told the truth. We can communicate on this theme. Here or in PM.