Related papers: A Computational Framework for Multi-Modal Social A…
Social media platforms have become a hub for political activities and discussions, democratizing participation in these endeavors. However, they have also become an incubator for manipulation campaigns, like information operations (IOs).…
We present a framework for large-scale sentiment and topic analysis of Twitter discourse. Our pipeline begins with targeted data collection using conflict-specific keywords, followed by automated sentiment labeling via multiple pre-trained…
Public institutions are increasingly reliant on data from social media sites to measure public attitude and provide timely public engagement. Such reliance includes the exploration of public views on important social issues such as…
In this project, we describe a method of modeling semantic leadership across a set of communities associated with the #BlackLivesMatter movement, which has been informed by qualitative research on the structure of social media and Black…
Social media users express their political preferences via interaction with other users, by spontaneous declarations or by participation in communities within the network. This makes a social network such as Twitter a valuable data source…
Current network-based methods for detecting coordinated inauthentic behaviour on social media focus primarily on inferring links between accounts based on common "behavioural traces" [19], such as retweeting the same tweet or posting the…
The 2016 United States presidential election has been characterized as a period of extreme divisiveness that was exacerbated on social media by the influence of fake news, trolls, and social bots. However, the extent to which the public…
A network is a composition of many communities, i.e., sets of nodes and edges with stronger relationships, with distinct and overlapping properties. Community detection is crucial for various reasons, such as serving as a functional unit of…
In this paper, We present our approach for IEEEBigMM 2020, Grand Challenge (BMGC), Identifying senti-ments from tweets related to the MeToo movement. The modelis based on an ensemble of Convolutional Neural Network,Bidirectional LSTM and a…
Social media provides a rich source of networked data. This data is represented by a set of nodes and a set of relations (edges). It is often possible to obtain or infer multiple types of relations from the same set of nodes, such as…
Opinions about the 2016 U.S. Presidential Candidates have been expressed in millions of tweets that are challenging to analyze automatically. Crowdsourcing the analysis of political tweets effectively is also difficult, due to large…
Social media, especially Twitter, is being increasingly used for research with predictive analytics. In social media studies, natural language processing (NLP) techniques are used in conjunction with expert-based, manual and qualitative…
With the rapid advancement of information and communication technologies, many researchers have adopted alternative data sources from private data vendors to study human movement dynamics in response to large-scale natural or societal…
Data on human spatial distribution and movement is essential for understanding and analyzing social systems. However existing sources for this data are lacking in various ways; difficult to access, biased, have poor geographical or temporal…
With the rise of Social Media, people obtain and share information almost instantly on a 24/7 basis. Many research areas have tried to gain valuable insights from these large volumes of freely available user generated content. With the goal…
People might not be close-at-hand but they still are - by virtue of the social network. The social network has transformed lives in many ways. People can express their views, opinions and life experiences on various platforms be it Twitter,…
Nowadays, many platforms on the Web offer organized events, allowing users to be organizers or participants. For such platforms, it is beneficial to predict potential event participants. Existing work on this problem tends to borrow…
Nowadays, people from all around the world use social media sites to share information. Twitter for example is a platform in which users send, read posts known as tweets and interact with different communities. Users share their daily…
Social media platforms are thriving nowadays, so a huge volume of data is produced. As it includes brief and clear statements, millions of people post their thoughts on microblogging sites every day. This paper represents and analyze the…
Social media provides many opportunities to monitor and evaluate political phenomena such as referendums and elections. In this study, we propose a set of approaches to analyze long-running political events on social media with a real-world…