A significant portion of data generated on blogging and microblogging websites is non-credible as shown in many recent studies. To filter out such non-credible information, machine learning can be deployed to build automatic credibility classifiers. However, as in the case with most supervised machine learning approaches, a sufficiently large and accurate training data must be available. In this paper, we focus on building a public Arabic corpus of blogs and microblogs that can be used for credibility classification. We focus on Arabic due to the recent popularity of blogs and microblogs in the Arab World and due to the lack of any such public corpora in Arabic. We discuss our data acquisition approach and annotation process, provide rigid ...
Arabic text sentiment analysis suffers from low accuracy due to Arabic-specific challenges (e.g., li...
International audienceSome users try to post false reviews to promote or to devalue other's products...
Online content posted by Arab users on social networks does not generally abide by the grammatical a...
Due to the large amount of information available on the web that is not necessarily true or believab...
Data generated on Twitter has become a rich source for various data mining tasks. Those data analysi...
Recent research in measuring web content credibility automatically for text and multimedia have addr...
Arabic news credibility on Twitter using sentiment analysis and ensemble learning. WHAT IS IT? ...
Different Natural Language Processing (NLP) applications such as text categorization, machine transl...
Over the years, social media has had a considerable impact on the way we share information and send ...
The news credibility detection task has started to gain more attention recently due to the rapid inc...
International audienceOver the last years, with the explosive growth of social media, huge amounts o...
Sentiment Analysis is achieved by using Natural Language Processing (NLP) techniques and finds wide ...
The ease of communication that has been made possible by chat messaging platforms, and their increas...
Mining publicly available data for meaning and value is an important research direction within soci...
Natural Language Processing (NLP) applications such as text categorization, machine translation, sen...
Arabic text sentiment analysis suffers from low accuracy due to Arabic-specific challenges (e.g., li...
International audienceSome users try to post false reviews to promote or to devalue other's products...
Online content posted by Arab users on social networks does not generally abide by the grammatical a...
Due to the large amount of information available on the web that is not necessarily true or believab...
Data generated on Twitter has become a rich source for various data mining tasks. Those data analysi...
Recent research in measuring web content credibility automatically for text and multimedia have addr...
Arabic news credibility on Twitter using sentiment analysis and ensemble learning. WHAT IS IT? ...
Different Natural Language Processing (NLP) applications such as text categorization, machine transl...
Over the years, social media has had a considerable impact on the way we share information and send ...
The news credibility detection task has started to gain more attention recently due to the rapid inc...
International audienceOver the last years, with the explosive growth of social media, huge amounts o...
Sentiment Analysis is achieved by using Natural Language Processing (NLP) techniques and finds wide ...
The ease of communication that has been made possible by chat messaging platforms, and their increas...
Mining publicly available data for meaning and value is an important research direction within soci...
Natural Language Processing (NLP) applications such as text categorization, machine translation, sen...
Arabic text sentiment analysis suffers from low accuracy due to Arabic-specific challenges (e.g., li...
International audienceSome users try to post false reviews to promote or to devalue other's products...
Online content posted by Arab users on social networks does not generally abide by the grammatical a...