Abdelwahed Motwakel^1,*, Hala J. Alshahrani², Jaber S. Alzahrani³, Ayman Yafoz⁴, Heba Mohsen⁵, Ishfaq Yaseen¹, Amgad Atta Abdelmageed¹, Mohamed I. Eldesouki⁶

Computer Systems Science and Engineering, Vol.47, No.3, pp. 2741-2757, 2023, DOI:10.32604/csse.2023.034721

Abstract Currently, individuals use online social media, namely Facebook or Twitter, for sharing their thoughts and emotions. Detection of emotions on social networking sites’ finds useful in several applications in social welfare, commerce, public health, and so on. Emotion is expressed in several means, like facial and speech expressions, gestures, and written text. Emotion recognition in a text document is a content-based classification problem that includes notions from deep learning (DL) and natural language processing (NLP) domains. This article proposes a Deer Hunting Optimization with Deep Belief Network Enabled Emotion Classification (DHODBN-EC) on English Twitter Data in this study. The presented… More >

Manar Ahmed Hamza^1,*, Hala J. Alshahrani², Khaled Tarmissi³, Ayman Yafoz⁴, Amal S. Mehanna⁵, Ishfaq Yaseen¹, Amgad Atta Abdelmageed¹, Mohamed I. Eldesouki⁶

Computer Systems Science and Engineering, Vol.46, No.3, pp. 3303-3319, 2023, DOI:10.32604/csse.2023.034823

Abstract The term ‘corpus’ refers to a huge volume of structured datasets containing machine-readable texts. Such texts are generated in a natural communicative setting. The explosion of social media permitted individuals to spread data with minimal examination and filters freely. Due to this, the old problem of fake news has resurfaced. It has become an important concern due to its negative impact on the community. To manage the spread of fake news, automatic recognition approaches have been investigated earlier using Artificial Intelligence (AI) and Machine Learning (ML) techniques. To perform the medicinal text classification tasks, the ML approaches were applied, and… More >