activity
20172024
most citedA review of sentiment analysis research in Arabic language

228 citations · 637 across the 45 of their papers we have counts for

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Showing 2019 · cs.CLShow all

7 papers · 2 filters

cs.CL2019

Business Taxonomy Construction Using Concept-Level Hierarchical Clustering

Haodong Bai, Frank Z. Xing, Erik Cambria +1

Business taxonomies are indispensable tools for investors to do equity research and make professional decisions. However, to identify the structure of industry sectors in an emergi…

cs.CL2019★ 30 cited

Towards Scalable and Reliable Capsule Networks for Challenging NLP Applications

Wei Zhao, Haiyun Peng, Steffen Eger +2

Obstacles hindering the development of capsule networks for challenging NLP applications include poor scalability to large output spaces and less reliable routing processes. In thi…

cs.CL2019

PhonSenticNet: A Cognitive Approach to Microtext Normalization for Concept-Level Sentiment Analysis

Ranjan Satapathy, Aalind Singh, Erik Cambria

With the current upsurge in the usage of social media platforms, the trend of using short text (microtext) in place of standard words has seen a significant rise. The usage of micr…

cs.CL2019

"Hang in There": Lexical and Visual Analysis to Identify Posts Warranting Empathetic Responses

Mimansa Jaiswal, Sairam Tabibu, Erik Cambria

In the past few years, social media has risen as a platform where people express and share personal incidences about abuse, violence and mental health issues. There is a need to pi…

cs.CL2019★ 2 cited

Aspect-Sentiment Embeddings for Company Profiling and Employee Opinion Mining

Rajiv Bajpai, Devamanyu Hazarika, Kunal Singh +3

With the multitude of companies and organizations abound today, ranking them and choosing one out of the many is a difficult and cumbersome task. Although there are many available…

cs.CL2019★ 5 cited

Phonetic-enriched Text Representation for Chinese Sentiment Analysis with Reinforcement Learning

Haiyun Peng, Yukun Ma, Soujanya Poria +2

The Chinese pronunciation system offers two characteristics that distinguish it from other languages: deep phonemic orthography and intonation variations. We are the first to argue…