Evidence map›Paper›PMID 28006016›Full record

ArticlePloS one2016

Measuring Emotion in Parliamentary Debates with Automated Textual Analysis.

Ludovic Rheault, Kaspar Beelen, Christopher Cochrane, Graeme Hirst

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

6 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. The ParlaMint corpora of parliamentary proceedings.Language resources and evaluation · 2023
    Article
  6. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors.

Ludovic RheaultDepartment of Political Science, University of Toronto, Toronto, Canada.
Kaspar BeelenInformatics Institute, University of Amsterdam, Amsterdam, Netherlands.
Christopher CochraneDepartment of Political Science, University of Toronto, Toronto, Canada.
Graeme HirstDepartment of Computer Science, University of Toronto, Toronto, Canada.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

An impressive breadth of interdisciplinary research suggests that emotions have an influence on human behavior. Nonetheless, we still know very little about the emotional states of those actors whose daily decisions have a lasting impact on our societies: politicians in parliament. We address this question by making use of methods of natural language processing and a digitized corpus of text data spanning a century of parliamentary debates in the United Kingdom. We use this approach to examine changes in aggregate levels of emotional polarity in the British parliament, and to test a hypothesis about the emotional response of politicians to economic recessions. Our findings suggest that, contrary to popular belief, the mood of politicians has become more positive during the past decades, and that variations in emotional polarity can be predicted by the state of the national economy.

Indexed as

BehaviorEmotionsNatural Language ProcessingPoliticsEconomicsGovernment EmployeesHumansUnited Kingdom

Identifiers

PMID28006016
PMCPMC5179059

What OpenQuestion holds

Textmetadata
LicenceCC BY
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Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.