Who and why Twitter users tweet on journal articles : a comparative analysis of readers of medicine and political science journal articles
Ever since its launch, Twitter has continued to attract a large base of technology-savvy users who enjoy the ease and convenience of networking, seeking and sharing information online. Scholars and publishers have come to recognize the potential of Twitter to promote, share and discuss scholarly wor...
Saved in:
Main Author: | |
---|---|
Other Authors: | |
Format: | Thesis-Master by Coursework |
Language: | English |
Published: |
Nanyang Technological University
2020
|
Subjects: | |
Online Access: | https://hdl.handle.net/10356/136624 |
Tags: |
Add Tag
No Tags, Be the first to tag this record!
|
Institution: | Nanyang Technological University |
Language: | English |
id |
sg-ntu-dr.10356-136624 |
---|---|
record_format |
dspace |
spelling |
sg-ntu-dr.10356-1366242020-01-08T02:55:14Z Who and why Twitter users tweet on journal articles : a comparative analysis of readers of medicine and political science journal articles Mohd Ismail Hussein Na Jin Cheon Wee Kim Wee School of Communication and Information TJCNa@ntu.edu.sg Library and information science::Libraries::Technologies Ever since its launch, Twitter has continued to attract a large base of technology-savvy users who enjoy the ease and convenience of networking, seeking and sharing information online. Scholars and publishers have come to recognize the potential of Twitter to promote, share and discuss scholarly work but have not yet fully understood who tweets about scholarly work and why they tweet about research articles. This study aimed to provide an insight on the type of people who tweet about research work and their motivations for doing so. It compared the profiles and purposes of Twitter users who tweet on medicine and political science articles to understand similarities and differences of tweets on two distinctively different disciplines. Tweets that mention scholarly work are extracted from Altmetric and Twitter. Content analysis and machine learning techniques were then applied to classify the type of Twitter users who originate these tweets, and to classify their motivation to tweet. The results from the study revealed that different disciplines attract different profiles of users. Medicine articles had a stronger appeal to the general public, while political science articles attracted a higher percentage of academics. The study also revealed that different user types have different motivations in using Twitter. Academics and publishers tended to capitalize on Twitter to promote their work, while non-academics mainly shared research work and to a lesser extent, expressed their opinions on the research. Master of Science (Information Studies) 2020-01-08T02:55:14Z 2020-01-08T02:55:14Z 2019 Thesis-Master by Coursework https://hdl.handle.net/10356/136624 en application/pdf Nanyang Technological University |
institution |
Nanyang Technological University |
building |
NTU Library |
country |
Singapore |
collection |
DR-NTU |
language |
English |
topic |
Library and information science::Libraries::Technologies |
spellingShingle |
Library and information science::Libraries::Technologies Mohd Ismail Hussein Who and why Twitter users tweet on journal articles : a comparative analysis of readers of medicine and political science journal articles |
description |
Ever since its launch, Twitter has continued to attract a large base of technology-savvy users who enjoy the ease and convenience of networking, seeking and sharing information online. Scholars and publishers have come to recognize the potential of Twitter to promote, share and discuss scholarly work but have not yet fully understood who tweets about scholarly work and why they tweet about research articles. This study aimed to provide an insight on the type of people who tweet about research work and their motivations for doing so. It compared the profiles and purposes of Twitter users who tweet on medicine and political science articles to understand similarities and differences of tweets on two distinctively different disciplines. Tweets that mention scholarly work are extracted from Altmetric and Twitter. Content analysis and machine learning techniques were then applied to classify the type of Twitter users who originate these tweets, and to classify their motivation to tweet. The results from the study revealed that different disciplines attract different profiles of users. Medicine articles had a stronger appeal to the general public, while political science articles attracted a higher percentage of academics. The study also revealed that different user types have different motivations in using Twitter. Academics and publishers tended to capitalize on Twitter to promote their work, while non-academics mainly shared research work and to a lesser extent, expressed their opinions on the research. |
author2 |
Na Jin Cheon |
author_facet |
Na Jin Cheon Mohd Ismail Hussein |
format |
Thesis-Master by Coursework |
author |
Mohd Ismail Hussein |
author_sort |
Mohd Ismail Hussein |
title |
Who and why Twitter users tweet on journal articles : a comparative analysis of readers of medicine and political science journal articles |
title_short |
Who and why Twitter users tweet on journal articles : a comparative analysis of readers of medicine and political science journal articles |
title_full |
Who and why Twitter users tweet on journal articles : a comparative analysis of readers of medicine and political science journal articles |
title_fullStr |
Who and why Twitter users tweet on journal articles : a comparative analysis of readers of medicine and political science journal articles |
title_full_unstemmed |
Who and why Twitter users tweet on journal articles : a comparative analysis of readers of medicine and political science journal articles |
title_sort |
who and why twitter users tweet on journal articles : a comparative analysis of readers of medicine and political science journal articles |
publisher |
Nanyang Technological University |
publishDate |
2020 |
url |
https://hdl.handle.net/10356/136624 |
_version_ |
1681038402491777024 |