The state of the art in sentiment visualization
Visualization of sentiments and opinions extracted from or annotated in texts has become a
prominent topic of research over the last decade. From basic pie and bar charts used to …
prominent topic of research over the last decade. From basic pie and bar charts used to …
Combining machine-learning topic models and spatiotemporal analysis of social media data for disaster footprint and damage assessment
Current disaster management procedures to cope with human and economic losses and to
manage a disaster's aftermath suffer from a number of shortcomings like high temporal lags …
manage a disaster's aftermath suffer from a number of shortcomings like high temporal lags …
Twitter sentiment analysis via bi-sense emoji embedding and attention-based LSTM
Sentiment analysis on large-scale social media data is important to bridge the gaps between
social media contents and real world activities including political election prediction …
social media contents and real world activities including political election prediction …
Bridging text visualization and mining: A task-driven survey
Visual text analytics has recently emerged as one of the most prominent topics in both
academic research and the commercial world. To provide an overview of the relevant …
academic research and the commercial world. To provide an overview of the relevant …
An agent-based model for emotion contagion and competition in online social media
R Fan, K Xu, J Zhao - Physica a: statistical mechanics and its applications, 2018 - Elsevier
Recent studies suggest that human emotions diffuse in not only real-world communities but
also online social media. However, a comprehensive model that considers up-to-date …
also online social media. However, a comprehensive model that considers up-to-date …
Multilingual opinion mining on YouTube–A convolutional N-gram BiLSTM word embedding
HT Nguyen, M Le Nguyen - Information Processing & Management, 2018 - Elsevier
Opinion mining in a multilingual and multi-domain environment as YouTube requires
models to be robust across domains as well as languages, and not to rely on linguistic …
models to be robust across domains as well as languages, and not to rely on linguistic …
Emotion-semantic-enhanced neural network
Although sentiment analysis on microblog posts has been studied in depth, sentiment
analysis of posts is still challenging because of the limited contextual information that they …
analysis of posts is still challenging because of the limited contextual information that they …
Analyzing and predicting emoji usages in social media
Emojis can be regarded as a language for graphical expression of emotions, and have been
widely used in social media. They can express more delicate feelings beyond textual …
widely used in social media. They can express more delicate feelings beyond textual …
Tales of emotion and stock in China: volatility, causality and prediction
Z Zhou, K Xu, J Zhao - World Wide Web, 2018 - Springer
How the online social media, like Twitter or its variant Weibo, interacts with the stock market
and whether it can be a convincing proxy to predict the stock market have been debated for …
and whether it can be a convincing proxy to predict the stock market have been debated for …
Sentiment analysis model on weather related tweets with deep neural network
J Qian, Z Niu, C Shi - Proceedings of the 2018 10th international …, 2018 - dl.acm.org
Weather related tweets are user's comments about daily weather. We can gain useful
information about how weather influence people's mood by analyzing them. This is what we …
information about how weather influence people's mood by analyzing them. This is what we …