Evidence map›Paper›PMID 39897900›Full record

ArticleHeliyon2025

Analyzing perception of Over-The-Top (OTT) sports broadcasting focus on social media big data analytics.

Wonyong Jang, Jaeyeon Hwang

Abstract read
In one paragraph

Article in Heliyon, 2025. 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
–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

0 citing papers in PubMed.

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

2 authors.

Wonyong JangResearch Institute for Regional Development, Kangwon National University, Samcheok, Gangwon, South Korea.
Jaeyeon HwangDepartment of Global Business, Kyungil University, Gyeongsan, Gyeongbuk, South Korea.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The purpose of this study was to analyze Korean subscribers' perceptions of sports broadcasting on OTT platforms. To achieve this, data was collected from various sources between 2018 and 2022 using 'OTT sports broadcasting' as the keyword, employing a big data processing solution called 'Textom.' The results were as follows: First, text mining was conducted to analyze word frequencies and examine TF-IDF scores. The text mining analysis revealed that words such as "broadcasting," "sports," "service," and "game" were used most frequently. In contrast, the TF-IDF analysis showed high scores for words like "SPOTV," "broadcasting," "Tottenham," and "live broadcast." Second, degree centrality and CONCOR analyses were employed for semantic analysis. The results indicated that degree centrality produced findings similar to the rankings based on word frequency. However, differences were observed in the rankings between degree centrality and TF-IDF. Next, a CONCOR analysis was conducted to explore the cluster relationships among words associated with the perception of 'OTT sports broadcasting.' This analysis resulted in the formation of four clusters consisting of words with similar characteristics: 'OTT soccer broadcasting,' 'Sports OTT platform,' 'OTT platform operator,' and 'Overseas sports broadcasting.'

Indexed as

Big dataOver-The-Top (OTT) platformSocial mediaSports broadcasting

Identifiers

PMID39897900
PMCPMC11787466

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.