Rumour Detection

111

The expansion of social networks has accelerated the transmission of information and news at every communities. Over the past few years, the number of users, audiences and social networking publishers, are increased dramatically too. Among the massive amounts of information and news reported on these networks, we are faced with issues that have not been verified which is called “rumors”. Identifying rumors on social networks is carried out in the form of rumor detection approaches; the massive amount of these news and information force to use the machine learning techniques. The most important problem with auto-detection approaches is the lack of a database of rumors. For that matter, in this article, a collection of rumors published on the social network “telegrams” have been collected. These data are gathered from five Persian-language channels that have specially reviewed this issue. The collected data set contains 3283 messages with 2829 attachments, having a volume of over 1.6 gigabytes. This dataset can also be used for different purposes of natural language processing.

FTR-18 is a multilingual rumour dataset on football transfer news. Transfer rumours are continuously published by sports media. They can both harm the image of player or a club or increase the player's market value. The proposed dataset includes transfer articles written in English, Spanish and Portuguese. It also comprises Twitter reactions related to the transfer rumours. FTR-18 is suited for rumour classification tasks and allows the research on the linguistic patterns used in sports journalism.

The CIDII dataset is a binary classification, consisting of two classes of correct information and disinformation related to Islamic issues. The CIDII dataset belongs to our research (DISINFORMATION DETECTION ABOUT ISLAMIC ISSUES ON SOCIAL MEDIA USING DEEP LEARNING TECHNIQUES) published in MJCS journal in the link below: https://ejournal.um.edu.my/index.php/MJCS/article/view/41935 This dataset consists of five columns: 1- ID: Each article has a unique ID. 2- Article: The article contains text that is either facts related to Islamic issues if the information is correct, or posts targeting the Islamic religion if the information is false. Most posts contain only the body without a title. 3- Propagation Source: The source refers to the source of the article content, as it contains a Facebook link in the event that the post is disinformation, or it contains a link to Islamic websites in the event that the article refers to correct information (an explanation of a verse, a hadith, or an article related to the Islamic religion). 4- Article Type: This column contains the type of article published. Is it a post if the article is disinformation, or is it an Islamic article, a Quranic interpretation, or a hadith, in case of that the information is correct? 5- Class Type: This column shows whether the article belongs to the category of correct information or disinformation.