Analysis of COVID-19-Related User Content on the Baseball Bulletin Board in 2020 through Text Mining.

Shang-Chun Ma, Ching-Ya Su, Sheng-Fong Chen, Shintaro Sato, Shang-Ming Ma

Open access · goldAbstract read

In one paragraph

Article in Behavioral sciences (Basel, Switzerland), 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it

0cells of the map it votes in

0citing papers in PubMed

0.5field-weighted citation impact, top 34% of its field

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

0 citing papers in PubMed, 1 citations in OpenAlex.

No citing paper in PubMed yet.

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

5 authors at 2 institutions in 2 countries.

Shang-Chun MaInstitute of Physical Education, Health and Leisure Studies, National Cheng Kung University, No. 1, Daxue Road, East District, Tainan 701401, Taiwan.ORCID 0000-0003-0691-6995

Ching-Ya SuInstitute of Physical Education, Health and Leisure Studies, National Cheng Kung University, No. 1, Daxue Road, East District, Tainan 701401, Taiwan.

Sheng-Fong ChenDepartment of Recreational Sport and Health Promotion, National Pingtung University of Science and Technology, No. 1, Shuefu Road, Neipu, Pingtung 912301, Taiwan.

Shintaro SatoFaculty of Sport Sciences, Waseda University, 3-4-1 Higashifushimi STEP22 Nishitokyo, Tokyo 202-0021, Japan.ORCID 0000-0003-3612-9001

Shang-Ming MaDepartment of Recreational Sport and Health Promotion, National Pingtung University of Science and Technology, No. 1, Shuefu Road, Neipu, Pingtung 912301, Taiwan.

National Pingtung University of Science and Technology · TWWaseda University · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The world engaged in online sport watching during COVID-19. Fortunately, in Taiwan, the pandemic was stably controlled in 2020, allowing for the continuation of the Chinese Professional Baseball League (CPBL); this attracted international attention and encouraged relevant discussions on social media in Taiwan. In the present study, through text mining, we analyzed user content (e.g., the concepts of sports service quality and social identity) on the Professional Technology Temple (PTT) baseball board-the largest online bulletin board system in Taiwan. A predictive model was constructed to assess PTT users' COVID-19-related comments in 2020. A total of 422 articles and 21,167 comments were retrieved. PTT users interacted more frequently during the closed-door period, particularly during the beginning of the CPBL in April. Effective pandemic prevention, which garnered global attention to the league, generated a sense of national identity among the users, which was strengthened with the development of peripheral products, such as English broadcasting and live broadcasting on Twitch. We used machine learning to develop a chatbot for predicting the attributes of users' comments; this chatbot may improve CPBL teams' understanding of public opinion trends. Our findings may help stakeholders develop tailored programs for online spectators of sports during pandemic situations.

Indexed as

baseballCOVID-19service qualitysocial identitysocial mediatext mining

Identifiers

PMID37503998

DOI10.3390/bs13070551

PMCPMC10376575

OpenAlexW4382940757

What OpenQuestion holds

Textmetadata

LicenceCC BY

Read underepoch 390

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.