Jumping NLP curves: A review of natural language processing research
E Cambria, B White - IEEE Computational intelligence …, 2014 - ieeexplore.ieee.org
Natural language processing (NLP) is a theory-motivated range of computational techniques
for the automatic analysis and representation of human language. NLP research has …
for the automatic analysis and representation of human language. NLP research has …
New avenues in opinion mining and sentiment analysis
New Avenues in Opinion Mining and Sentiment Analysis Page 1 New Avenues in Opinion
Mining and Sentiment Analysis Erik Cambria, Member, IEEE, Björn Schuller, Member, IEEE …
Mining and Sentiment Analysis Erik Cambria, Member, IEEE, Björn Schuller, Member, IEEE …
Affective computing and sentiment analysis
E Cambria, D Das, S Bandyopadhyay… - A practical guide to …, 2017 - Springer
Understanding emotions is one of the most important aspects of personal development and
growth and, as such, it is a key tile for the emulation of human intelligence. Besides being a …
growth and, as such, it is a key tile for the emulation of human intelligence. Besides being a …
Bidirectional LSTM with self-attention mechanism and multi-channel features for sentiment classification
W Li, F Qi, M Tang, Z Yu - Neurocomputing, 2020 - Elsevier
There are a lot of linguistic knowledge and sentiment resources nowadays, but in the current
research with deep learning framework, these kinds of unique sentiment information are not …
research with deep learning framework, these kinds of unique sentiment information are not …
SenticNet 3: a common and common-sense knowledge base for cognition-driven sentiment analysis
E Cambria, D Olsher, D Rajagopal - … of the AAAI conference on artificial …, 2014 - ojs.aaai.org
SenticNet is a publicly available semantic and affective resource for concept-level sentiment
analysis. Rather than using graph-mining and dimensionality-reduction techniques …
analysis. Rather than using graph-mining and dimensionality-reduction techniques …
The determinants of crowdfunding success: A semantic text analytics approach
H Yuan, RYK Lau, W Xu - Decision Support Systems, 2016 - Elsevier
In the era of the Social Web, crowdfunding has become an increasingly more important
channel for entrepreneurs to raise funds from the crowd to support their startup projects …
channel for entrepreneurs to raise funds from the crowd to support their startup projects …
Data mining techniques in social media: A survey
Today, the use of social networks is growing ceaselessly and rapidly. More alarming is the
fact that these networks have become a substantial pool for unstructured data that belong to …
fact that these networks have become a substantial pool for unstructured data that belong to …
Social media analytics on Russia–Ukraine cyber war with natural language processing: Perspectives and challenges
F Sufi - Information, 2023 - mdpi.com
Utilizing social media data is imperative in comprehending critical insights on the Russia–
Ukraine cyber conflict due to their unparalleled capacity to provide real-time information …
Ukraine cyber conflict due to their unparalleled capacity to provide real-time information …
Social emotion classification of short text via topic-level maximum entropy model
With the rapid proliferation of Web 2.0, the identification of emotions embedded in user-
contributed comments at the social web is both valuable and essential. By exploiting large …
contributed comments at the social web is both valuable and essential. By exploiting large …
Learning user and product distributed representations using a sequence model for sentiment analysis
In product reviews, it is observed that the distribution of polarity ratings over reviews written
by different users or evaluated based on different products are often skewed in the real …
by different users or evaluated based on different products are often skewed in the real …