相关论文: TEVISE: An Interactive Visual Analytics Tool to Ex…
Twitter is one of the popular social media platforms where people share news or reactions towards an event or topic using short text messages called "tweets". Emotion analysis in these tweets can play a vital role in understanding peoples'…
This paper introduces a large collection of time series data derived from Twitter, postprocessed using word embedding techniques, as well as specialized fine-tuned language models. This data comprises the past five years and captures…
The present study proposes a novel method of trend detection and visualization - more specifically, modeling the change in a topic over time. Where current models used for the identification and visualization of trends only convey the…
When researchers are about to start a new project or have just entered a new research field, choosing a proper research topic is always challenging. To help them have an overall understanding of the research trend in real-time and find out…
The social media craze is on an ever increasing spree, and people are connected with each other like never before, but these vast connections are visually unexplored. We propose a methodology Twigraph to explore the connections between…
Analyzing how interrelated ideas flow within and between multiple social groups helps understand the propagation of information, ideas, and thoughts on social media. The existing dynamic text analysis work on idea flow analysis is mostly…
Social media is often used by researchers as an approach to obtaining real-time data on people's activities and thoughts. Twitter, as one of the most popular social networking services nowadays, provides copious information streams on…
Temporal (or time-evolving) networks are commonly used to model complex systems and the evolution of their components throughout time. Although these networks can be analyzed by different means, visual analytics stands out as an effective…
Tracking and collecting fast-evolving online discussions provides vast data for studying social media usage and its role in people's public lives. However, collecting social media data using a static set of keywords fails to satisfy the…
With the increasing demands on e-commerce platforms, numerous user action history is emerging. Those enriched action records are vital to understand users' interests and intents. Recently, prior works for user behavior prediction mainly…
Many processes, from gene interaction in biology to computer networks to social media, can be modeled more precisely as temporal hypergraphs than by regular graphs. This is because hypergraphs generalize graphs by extending edges to connect…
Rapid improvements in the performance of machine learning models have pushed them to the forefront of data-driven decision-making. Meanwhile, the increased integration of these models into various application domains has further highlighted…
Dynamic topic modeling is useful at discovering the development and change in latent topics over time. However, present methodology relies on algorithms that separate document and word representations. This prevents the creation of a…
Recent research in opinion mining proposed word embedding-based topic modeling methods that provide superior coherence compared to traditional topic modeling. In this paper, we demonstrate how these methods can be used to display correlated…
The many endless rivers of text now available present a serious challenge in the task of gleaning, analyzing and discovering useful information. In this paper, we describe a methodology for visualizing text streams in real time. The…
For large volumes of text data collected over time, a key knowledge discovery task is identifying and tracking clusters. These clusters may correspond to emerging themes, popular topics, or breaking news stories in a corpus. Therefore,…
Language features are evolving in real-world social media, resulting in the deteriorating performance of text classification in dynamics. To address this challenge, we study temporal adaptation, where models trained on past data are tested…
We present the results of a comprehensive analysis of visualization paper keywords supplied for 4366 papers submitted to five main visualization conferences. We describe main keywords, topic areas, and 10-year historic trends from two…
Social media platforms contain a great wealth of information which provides opportunities for us to explore hidden patterns or unknown correlations, and understand people's satisfaction with what they are discussing. As one showcase, in…
The continued improvements in the predictive accuracy of machine learning models have allowed for their widespread practical application. Yet, many decisions made with seemingly accurate models still require verification by domain experts.…