... and individual cognition and how deep learning techniques can enhance our understanding of the semantic structures within folksonomies. Design/methodology/approach Popular tags from three benchmark years (2006, 2010 and 2015) were collected and manually categorized using a faceted classification scheme...

... the interplay between social media dynamics and Pakistan’s political landscape. The proposed hybrid model combines supervised machine learning and deep learning for Twitter-based text classification to assess political perceptions. A total of 52,067 tweets were analyzed and categorized into eight emotion groups...

... using the approach of machine and deep learning. Design/methodology/approach For the purpose of sarcasm detection, machine and deep learning models were used on a data set consisting of 1.3 million social media comments, including both sarcastic and non-sarcastic comments. The data set was pre...

... and many of the latest deep learning (DL) algorithms (Wu et al., 2007). Past research has investigated several FinTech applications adopting data mining technologies, such as personal bankruptcy prediction (Nor et al., 2019), financial distress prediction (Huang and Yen, 2019...

...: a list of keywords used in research papers and search query/term used during the search. Table 1 Identified key words Key words Log, events, log analysis, failure detection, failure prediction, machine learning, Deep Learning Search query/term ((“Events” OR “System log” OR “Event...

... learning and deep learning (DL) models in predictive analytics that include both behaviors and text analysis. Design/methodology/approach This study combined behavioral data and discussion board content to construct early warning models with machine learning and DL algorithms. In total, 680 course...