Evidence map›Paper›PMID 37666917›Full record

ArticleScientific reports2023

Conversational agents enhance women's contribution in online debates.

Rafik Hadfi, Shun Okuhara, Jawad Haqbeen, Sofia Sahab, Susumu Ohnuma, Takayuki Ito

Abstract read
In one paragraph

Article in Scientific reports, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Review
  2. Review
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

6 authors.

Rafik HadfiDepartment of Social Informatics, Kyoto University, Kyoto, Japan. rafik.hadfi@i.kyoto-u.ac.jp.
Shun OkuharaGraduate School of Engineering, Mie University, Tsu, Mie, Japan.
Jawad HaqbeenDepartment of Social Informatics, Kyoto University, Kyoto, Japan.
Sofia SahabDepartment of Social Informatics, Kyoto University, Kyoto, Japan.
Susumu OhnumaDepartment of Behavioral Science, Hokkaido University, Sapporo, Japan.
Takayuki ItoDepartment of Social Informatics, Kyoto University, Kyoto, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The advent of Artificial Intelligence (AI) is fostering the development of innovative methods of communication and collaboration. Integrating AI into Information and Communication Technologies (ICTs) is now ushering in an era of social progress that has the potential to empower marginalized groups. This transformation paves the way to a digital inclusion that could qualitatively empower the online presence of women, particularly in conservative and male-dominated regions. To explore this possibility, we investigated the effect of integrating conversational agents into online debates encompassing 240 Afghans discussing the fall of Kabul in August 2021. We found that the agent leads to quantitative differences in how both genders contribute to the debate by raising issues, presenting ideas, and articulating arguments. We also found increased ideation and reduced inhibition for both genders, particularly females, when interacting exclusively with other females or the agent. The enabling character of the conversational agent reveals an apparatus that could empower women and increase their agency on online platforms.

Indexed as

Artificial IntelligenceCommunicationFemaleHumansInhibition, PsychologicalMaleMental Processes

Identifiers

PMID37666917
PMCPMC10477209

What OpenQuestion holds

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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.