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On Classifying whether Two Texts are on the Same Side of an Argument ...
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AWESSOME : An unsupervised sentiment intensity scoring framework using neural word embeddings
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Abstract:
Sentiment analysis (SA) is the key element for a variety of opinion and attitude mining tasks. While various unsupervised SA tools already exist, a central problem is that they are lexicon-based where the lexicons used are limited, leading to a vocabulary mismatch. In this paper, we present an unsupervised word embedding-based sentiment scoring framework for sentiment intensity scoring (SIS). The framework generalizes and combines past works so that pre-existing lexicons (e.g. VADER, LabMT) and word embeddings (e.g. BERT, RoBERTa) can be used to address this problem, with no require training, and while providing fine grained SIS of words and phrases. The framework is scalable and extensible, so that custom lexicons or word embeddings can be used to core methods, and to even create new corpus specific lexicons without the need for extensive supervised learning and retraining. The Python 3 toolkit is open source, freely available from GitHub (https://github.com/cumulative-revelations/awessome ) and can be directly installed via pip install awessome.
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Keyword:
Electronic computers. Computer science
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URL: https://strathprints.strath.ac.uk/75996/
https://doi.org/10.1007/978-3-030-72240-1_56
https://strathprints.strath.ac.uk/75996/1/Htait_Azzopardi_ECIR_2021_AWESSOME_an_unsupervised_sentiment_intensity_scoring_framework.pdf
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Evaluating multilingual text encoders for unsupervised cross-lingual retrieval
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Webis Argument Quality Corpus 2020 (Webis-ArgQuality-20) ...
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Webis Argument Quality Corpus 2020 (Webis-ArgQuality-20) ...
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Overview of PAN 2020: Authorship Verification, Celebrity Profiling, Profiling Fake News Spreaders on Twitter, and Style Change Detection
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Overview of PAN 2019: Bots and Gender Profiling, Celebrity Profiling, Cross-domain Authorship Attribution and Style Change Detection
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Overview of PAN 2018. Author identification, author profiling, and author obfuscation
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CoNLL 2017 Shared Task: Multilingual Parsing from Raw Text to Universal Dependencies
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Overview of PAN'17: Author Identification, Author Profiling, and Author Obfuscation
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