Topic modeling for social media content: A practical approach

Unsupervised Labor Intelligence Systems: A Detection Approach and Its Evaluation

“…Shahbazi et al [32] collected contents from different social media to conduct a semi-automatic process. Rohani et al [30] addressed the problem to detect topics from a large variety of semantic text by proposing a topic modeling technique based on LDA. Statistical topic modeling based on LDA is also effective in crime prediction.…”

“…After extracting the data, we tried to find the essential information that characterizes online job advertisements using topic modeling., possibly spotting potential signals of labor exploitation. The usage of topic modeling showed promising results in uncovering hidden communities of tweets in social media [30]. We exploited two topic modeling techniques, Latent Dirichlet Allocation (LDA) and Latent Semantic Indexing (LSI).…”

Survey on data analysis in social media: A practical application aspect

“…Cataldi et al [18] mentioned that "Twitter defines a low-level information news flashes portal". Even if it cannot be considered [18] Queries Create a navigable topic graph with emerging topics over time 2010 Sizov [19] Topic modeling GeoFolk to discover latent topics 2010 Song et al [20] Topic modeling Explore spatio-temporal framework for related topic search 2012 Han and Kang [21] Queries Identify the personalized relevance of social issues to targets 2012 Song et al [22] Topic modeling Identify the personalized relevance of social issues to targets 2012 Hu et al [23] Topic modeling Propose a topic modeling with user features 2013 Kamath et al [24] Hashtags Study the spatio-temporal dynamics of Twitter hashtags 2013 Ma et al [25] Topic modeling Propose Tag-Latent Dirichlet Allocation (TLDA) to bridge hash tags and topics 2013 Bogdanov et al [26] Topic modeling Identify the personalized relevance of social issues to targets 2015 Jang and Myaeng [27] Topic modeling Analyze spatially oriented topic versatility 2015 Yao et al [28] Topic modeling Analyze news trends in Twitter 2016 Qian et al [29] Topic modeling Analyze multi-model event topic model 2016 Musaev and Hou [30] Queries Detect landslides with Twitter data 2016 Rohani et al [31] Topic modeling Explore an unsupervised topic modeling approach 2018 Argyrou et al [32] Hashtags Prepare training images for Automatic Image Annotation (AIA) 2018 Ejaz et al [33] Topic modeling Analyze news using ontology…”

“…LDA is a popular topic modeling technique. In the hope to improve the accuracy, researchers are extending LDA by incorporating additional information, such as hashtags, user profiles, and location information [31] . Ma et al [25] proposed TLDA to bridge hashtags and topics.…”