Related papers: Entity Graphs for Exploring Online Discourse
Knowledge is captured in the form of entities and their relationships and stored in knowledge graphs. Knowledge graphs enhance the capabilities of applications in many different areas including Web search, recommendation, and natural…
The proliferation of public networks has enabled instantaneous and interactive communication that transcends temporal and spatial constraints. The vast amount of textual data on the Web has facilitated the study of quantitative analysis of…
The massive amount of text data on the web has facilitated research on the quantitative analysis of public opinion, which could not be visualized earlier. In this paper, we propose a new opinion dynamics theory. This theory that is intended…
Human conversation is organized by an implicit chain of thoughts that manifests as timed speech acts. Capturing this causal pathway is key to building natural full-duplex interactive systems. We introduce a framework that enables reasoning…
Online social media has become increasingly popular in recent years due to its ease of access and ability to connect with others. One of social media's main draws is its anonymity, allowing users to share their thoughts and opinions without…
This paper aims to show how some popular topics on social networks can be used to predict online newspaper views, related to the topics. Newspapers site and many social networks, become a good source of data to analyse and explain complex…
Online social networks are a dominant medium in everyday life to stay in contact with friends and to share information. In Twitter, users can connect with other users by following them, who in turn can follow back. In recent years,…
How does political discourse spread in digital networks? Can we empirically test if certain conceptual frames of social movements have a correlate on their online discussion networks? Through an analysis of the Twitter data from the Occupy…
The broad adoption of online social networking platforms has made it possible to study communication networks at an unprecedented scale. Digital trace data can be compiled into large data sets of online discourse. However, it is a challenge…
Which topics spark the most heated debates on social media? Identifying those topics is not only interesting from a societal point of view, but also allows the filtering and aggregation of social media content for disseminating news…
The enormous increase of popularity and use of the WWW has led in the recent years to important changes in the ways people communicate. An interesting example of this fact is provided by the now very popular social annotation systems,…
Conversational machine comprehension (MC) has proven significantly more challenging compared to traditional MC since it requires better utilization of conversation history. However, most existing approaches do not effectively capture…
Millions of people use online social networks to reinforce their sense of belonging, for example by giving and asking for feedback as a form of social validation and self-recognition. It is common to observe disagreement among people…
Machine learning about language can be improved by supplying it with specific knowledge and sources of external information. We present here a new version of the linked open data resource ConceptNet that is particularly well suited to be…
This paper presents a novel approach for modeling threaded discussions on social media using a graph-structured bidirectional LSTM which represents both hierarchical and temporal conversation structure. In experiments with a task of…
We propose a system to predict harmful discussions on social media platforms. Our solution uses contextual deep language models and proposes the novel idea of integrating state-of-the-art Graph Transformer Networks to analyze all…
Online forums are rich sources of information about user communication activity over time. Finding temporal patterns in online forum communication threads can advance our understanding of the dynamics of conversations. The main challenge of…
Online users discuss and converse about all sorts of topics on social networks. Facebook, Twitter, Reddit are among many other networks where users can have this freedom of information sharing. The abundance of information shared over these…
Navigating large-scale online discussions is difficult due to the rapid pace and large volume of user-generated content. Prior work in CSCW has shown that moderators often struggle to follow multiple simultaneous discussions, track evolving…
Organizations generate vast amounts of interconnected content across various platforms. While language models enable sophisticated reasoning for use in business applications, retrieving and contextualizing information from organizational…