Twitter and research: A systematic literature review through text mining
Researchers have collected Twitter data to study a wide range of topics. This growing body
of literature, however, has not yet been reviewed systematically to synthesize Twitter-related …
of literature, however, has not yet been reviewed systematically to synthesize Twitter-related …
Latent Dirichlet allocation (LDA) and topic modeling: models, applications, a survey
Topic modeling is one of the most powerful techniques in text mining for data mining, latent
data discovery, and finding relationships among data and text documents. Researchers …
data discovery, and finding relationships among data and text documents. Researchers …
Discourse-aware rumour stance classification in social media using sequential classifiers
Rumour stance classification, defined as classifying the stance of specific social media posts
into one of supporting, denying, querying or commenting on an earlier post, is becoming of …
into one of supporting, denying, querying or commenting on an earlier post, is becoming of …
DRI-RCNN: An approach to deceptive review identification using recurrent convolutional neural network
W Zhang, Y Du, T Yoshida, Q Wang - Information Processing & …, 2018 - Elsevier
With the widespread of deceptive opinions in the Internet, how to identify online deceptive
reviews automatically has become an attractive topic in research field. Traditional methods …
reviews automatically has become an attractive topic in research field. Traditional methods …
Mining user interests over active topics on social networks
Inferring users' interests from their activities on social networks has been an emerging
research topic in the recent years. Most existing approaches heavily rely on the explicit …
research topic in the recent years. Most existing approaches heavily rely on the explicit …
A bibliometric analysis of event detection in social media
A bibliometric analysis of event detection in social media | Emerald Insight Books and
journals Case studies Expert Briefings Open Access Publish with us Advanced search A …
journals Case studies Expert Briefings Open Access Publish with us Advanced search A …
Real-time event detection in social media streams through semantic analysis of noisy terms
Interactions via social media platforms have made it possible for anyone, irrespective of
physical location, to gain access to quick information on events taking place all over the …
physical location, to gain access to quick information on events taking place all over the …
A survey on event and subevent detection from microblog data towards crisis management
SR Chowdhury, S Basu, U Maulik - … Journal of Data Science and Analytics, 2022 - Springer
Social media data analysis is a popular research domain since the last decade. Detecting
the events and sub-events from social media posts that require special attention is one of the …
the events and sub-events from social media posts that require special attention is one of the …
Modeling islamist extremist communications on social media using contextual dimensions: religion, ideology, and hate
Terror attacks have been linked in part to online extremist content. Online conversations are
cloaked in religious ambiguity, with deceptive intentions, often twisted from mainstream …
cloaked in religious ambiguity, with deceptive intentions, often twisted from mainstream …
Event mining and timeliness analysis from heterogeneous news streams
News documents published online represent an important source of information that can be
used for event detection and tracking as well as for analyzing the temporal publishing …
used for event detection and tracking as well as for analyzing the temporal publishing …