Sentiment and position-taking analysis of parliamentary debates: a systematic literature review

Author:

Abercrombie GavinORCID,Batista-Navarro Riza

Abstract

AbstractParliamentary and legislative debate transcripts provide access to information concerning the opinions, positions, and policy preferences of elected politicians. They attract attention from researchers from a wide variety of backgrounds, from political and social sciences to computer science. As a result, the problem of computational sentiment and position-taking analysis has been tackled from different perspectives, using varying approaches and methods, and with relatively little collaboration or cross-pollination of ideas. The existing research is scattered across publications from various fields and venues. In this article, we present the results of a systematic literature review of 61 studies, all of which address the automatic analysis of the sentiment and opinions expressed, and the positions taken by speakers in parliamentary (and other legislative) debates. In this review, we discuss the existing research with regard to the aims and objectives of the researchers who work in this area, the automatic analysis tasks which they undertake, and the approaches and methods which they use. We conclude by summarizing their findings, discussing the challenges of applying computational analysis to parliamentary debates, and suggesting possible avenues for further research.

Publisher

Springer Science and Business Media LLC

Subject

General Earth and Planetary Sciences,General Environmental Science

Reference81 articles.

1. Abercrombie, G., & Batista-Navarro, R. (2018). ‘Aye’ or ‘no’? Speech-level sentiment analysis of Hansard UK parliamentary debate transcripts. In: Proceedings of the eleventh international conference on language resources and evaluation (LREC-2018). European Languages Resources Association (ELRA), Miyazaki, Japan. https://www.aclweb.org/anthology/L18-1659.

2. Abercrombie, G., & Batista-Navarro, R.T. (2018). Identifying opinion-topics and polarity of parliamentary debate motions. In: Proceedings of the 9th workshop on computational approaches to subjectivity, sentiment and social media analysis. Association for Computational Linguistics, Brussels, Belgium (pp. 280–285). https://doi.org/10.18653/v1/W18-6241. https://www.aclweb.org/anthology/W18-6241.

3. Ahmadalinezhad, M., & Makrehchi, M. (2018). Detecting agreement and disagreement in political debates. In R. Thomson, C. Dancy, A. Hyder, & H. Bisgin (Eds.), Social, cultural, and behavioral modeling (pp. 54–60). Cham: Springer.

4. Akhmedova, S., Semenkin, E., & Stanovov, V. (2018). Co-operation of biology related algorithms for solving opinion mining problems by using different term weighting schemes. In: K. Madani, D. Peaucelle, O. Gusikhin (Eds.) Informatics in control, automation and robotics: 13th international conference, ICINCO 2016 Lisbon, Portugal, 29-31 July, 2016 (pp. 73–90). Cham: Springer. https://doi.org/10.1007/978-3-319-55011-4_4.

5. Allison, B. (2008). Sentiment detection using lexically-based classifiers. In P. Sojka, A. Horák, I. Kopeček, & K. Pala (Eds.), Text, speech and dialogue (pp. 21–28). Berlin: Springer.

Cited by 23 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Nationalistic political rhetoric: measurement and preliminary insights;Journal of International Management;2023-11

2. Open framework for analyzing public parliaments data;Journal of Big Data;2023-10-19

3. Identifying Euroscepticism Using a Text-As-Data Approach: An Experimental Study Employing Parliamentary Speeches;2023 18th International Workshop on Semantic and Social Media Adaptation & Personalization (SMAP)18th International Workshop on Semantic and Social Media Adaptation & Personalization (SMAP 2023);2023-09-25

4. Issue Responsiveness in Canadian Politics: Are Parties Responsive to the Public Salience of Climate Change in the Question Period?;Political Research Quarterly;2023-09-06

5. The partisan foundations of parliamentary speech. How parliamentary party groups decide who gets to speak for them;Party Politics;2023-07-13

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3