Abstract
The spreading of accidental or malicious misinformation on social media, specifically in critical situations, such as real-world emergencies, can have negative consequences for society. This facilitates the spread of rumors on social media. On social media, users share and exchange the latest information with many readers, including a large volume of new information every second. However, updated news sharing on social media is not always true.In this study, we focus on the challenges of numerous breaking-news rumors propagating on social media networks rather than long-lasting rumors. We propose new social-based and content-based features to detect rumors on social media networks. Furthermore, our findings show that our proposed features are more helpful in classifying rumors compared with state-of-the-art baseline features. Moreover, we apply bidirectional LSTM-RNN on text for rumor prediction. This model is simple but effective for rumor detection. The majority of early rumor detection research focuses on long-running rumors and assumes that rumors are always false. In contrast, our experiments on rumor detection are conducted on real-world scenario data set. The results of the experiments demonstrate that our proposed features and different machine learning models perform best when compared to the state-of-the-art baseline features and classifier in terms of precision, recall, and F1 measures.
Highlights
The social media platform is rapidly growing day by day
The output of this algorithm is depicted in Figure 6 where it can be seen that Support Vector Machine (SVM) performs best in terms with precision 0.41, recall 0.53, and F1
Most of the existing work on rumor identification from social media relies on manually extracting features or rules
Summary
The social media platform is rapidly growing day by day. The pew research center [1]stated that in august 2017, 67% of Americans received new information from social media platforms and 74% of twitter users obtained their news from the website. The social media platform is rapidly growing day by day. The pew research center [1]. Stated that in august 2017, 67% of Americans received new information from social media platforms and 74% of twitter users obtained their news from the website. Especially twitter, is the primary source of posting and sharing the latest updates that come from the fact that anyone can share. Twitter has a monthly active social media presence of 330 million and a daily active number of users of approximately 145 million. Users share and exchange the latest information with many readers, including a large volume of new information every second
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