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2019 ACL ACL 2019

Investigating Political Herd Mentality: A Community Sentiment Based Approach

Abstract

AbstractAnalyzing polarities and sentiments inherent in political speeches and debates poses an important problem today. This experiment aims to address this issue by analyzing publicly-available Hansard transcripts of the debates conducted in the UK Parliament. Our proposed approach, which uses community-based graph information to augment hand-crafted features based on topic modeling and emotion detection on debate transcripts, currently surpasses the benchmark results on the same dataset. Such sentiment classification systems could prove to be of great use in today’s politically turbulent times, for public knowledge of politicians’ stands on various relevant issues proves vital for good governance and citizenship. The experiments also demonstrate that continuous feature representations learned from graphs can improve performance on sentiment classification tasks significantly.

🌱 Topic Pioneer — Graph Neural Networks
🌉 Interdisciplinary Bridge — Deep Learning and Machine Learning and Natural Language Processing
🧭 Keyword Pioneer — political text
🐣 Hot Topic Early Bird — sentiment analysis
🐝 Cross-Pollinator — Artificial Intelligence, Computer Science, Computer Vision, Data Science & Analytics, Deep Learning, Interdisciplinary, Knowledge & Reasoning, Machine Learning, Mathematics & Optimization, Natural Language Processing, Reinforcement Learning

Authors

Anjali Bhavan , Rohan Mishra , Pradyumna Prakhar Sinha , Ramit Sawhney , Rajiv Ratn Shah

Topics

Machine Learning > Core Methods > Classification Deep Learning > Architectures > Graph Neural Networks Natural Language Processing > Understanding > Sentiment Analysis Natural Language Processing > Applications > Sentiment Analysis Machine Learning > Core Methods > Graph Neural Networks Deep Learning > Learning Types > Representation Learning

Keywords

sentiment analysis text classification topic modeling graph representation community detection emotion detection graph embedding political text political analysis
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