Towards the measurement of Arabic Weblogs credibility automatically

Al-Eidan, Rasha M. BinSultan; Al‐Khalifa, Hend S.; Al-Salman, AbdulMalik S.

doi:10.1145/1806338.1806455

Cited by 8 publications

(8 citation statements)

References 19 publications

(23 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Furthermore, there are many systems developed for credibility detection that are limited in their applications; for instance, TweetCred [56] is implemented as a Chrome plugin. However, Gupta et al [56] noted that their tool is experimental and will improve over time. In addition, its feedback is not automatic, as it is received from users.…”

Section: Discussionmentioning

confidence: 99%

“…In summary, the accuracy of automated and semi-automated techniques still has much room for improvement. In a work by Al-Khalifa and associates [29], [56] a new technique is discussed grounded on overlapping of tweets with already confirmed sources. The technique faces several significant issues.…”

Section: Discussionmentioning

confidence: 99%

“…Most investigations have automatically measured credibility for English, German, and Japanese web content. Al-Eidan et al [56], published in 2009, was the first work for Arabic in this domain, followed by another paper by Al-Khalifa and Al-Eidan [29] in 2011 that improved upon their previous work. They used an evidence-based method that allowed them to compare content with trusted news sources using NLP.…”

Section: Weighted and Ir Algorithmsmentioning

confidence: 98%

“…Several other researchers have implemented machine learning techniques as systems to assess credibility for both real-time and offline social network content. Al-Eidan et al [56] developed an automatic credibility measurement system for Arabic web content. The system classifies Arabic weblogs based on selected features into three classes: believable, not believable, and doubtful.…”

Section: Graph-based and Semi-supervised Algorithmsmentioning

confidence: 99%

See 3 more Smart Citations

Credibility in Online Social Networks: A Survey

et al. 2019

View full text Add to dashboard Cite

The importance of information credibility in society cannot be underestimated given that it is at the heart of all decision-making. Generally, more information is better; however, knowing the value of this information is essential for the decision-making processes. Information credibility defines a measure of the fitness of the information for consumption. It can also be defined in terms of reliability, which denotes the probability that a data source will appear credible to the users. A challenge in this topic is that there is a great deal of literature that has developed different credibility dimensions. In addition, information science dealing with online social networks has grown in complexity, attracting interest from researchers in information science, psychology, human-computer interaction, communication studies, and management studies, all of whom have studied the topic from different perspectives. This work will attempt to provide an overall review of the credibility assessment literature over the period 2006-2017 as applied to the context of the microblogging platform, Twitter. The known interpretations of credibility will be examined, particularly as they relate to the Twitter environment. In addition, we investigate levels of credibility assessment features. We then discuss recent works, addressing a new taxonomy of credibility analysis and assessment techniques. At last, a cross-referencing of literature is performed while suggesting new topics for future studies of credibility assessment in a social media context.

show abstract

Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

Section: Weighted and Ir Algorithmsmentioning

confidence: 98%

Section: Graph-based and Semi-supervised Algorithmsmentioning

confidence: 99%

See 2 more Smart Citations

Credibility in Online Social Networks: A Survey

et al. 2019

View full text Add to dashboard Cite

show abstract

“…Al-Eidan, Rasha M. BinSultan et al [21], proposed a system to measure information credibility of Arabic web content automatically focused on weblogs and need to enhance the selected credibility features by using SVM machine learning technique to be suitable for the Arabic language.…”

Section: Related Workmentioning

confidence: 99%

A Multi-dimensional Credibility Assessment for Arabic News Sources

Gaber¹,

El-din²,

Moussa³

2021

IJACSA

View full text Add to dashboard Cite

Due to the advances in social media, it has become the most popular means of the propagation of news. Many news items are published on social media like Facebook, Twitter, Instagram, etc. Facebook is a huge source for spreading and consuming daily news, but it is an unstructured way of producing news about domains (Art, Health, Education, Sport, Politics, etc.). Thus, this paper will present a model to assess the credibility of news sources over the social context in a particular domain through a particular period of time from a multidimensional perspective. Based on these dimensions of credibility, this model will be designed, evaluated, and implemented by using machine learning algorithms and Arabic NLP approaches to assess the credibility score for Arabic news sources on Facebook. In addition, the study will visualize their scores at different data analysis levels to make the assessment more precise and trustworthy. The proposed model has been implemented and tested over some real Arabic news sources for specific domains and over a period of time to produce a credibility score for each one, whereas the user can display these scores and choose the most credible news sources. The credibility assessment model will be more specific and accurate for a specific domain and time with an accuracy of 98%.

show abstract

Automating Credibility Assessment of Arabic News

Hammad

Hemayed

2013

Lecture Notes in Computer Science

View full text Add to dashboard Cite

Towards the measurement of Arabic Weblogs credibility automatically

Cited by 8 publications

References 19 publications

Credibility in Online Social Networks: A Survey

Credibility in Online Social Networks: A Survey

A Multi-dimensional Credibility Assessment for Arabic News Sources

Automating Credibility Assessment of Arabic News

Contact Info

Product

Resources

About