Tampere University of Technology

TUTCRIS Research Portal

Who contributes what? Scrutinizing the activity data of 4.2 million Zhihu users via immersion scores

Research output: Contribution to journalArticleScientificpeer-review

Standard

Who contributes what? Scrutinizing the activity data of 4.2 million Zhihu users via immersion scores. / Deng, Shengli; Jiang, Yuting; Li, Hongxiu; Liu, Yong.

In: INFORMATION PROCESSING AND MANAGEMENT, Vol. 57, No. 5, 102274, 2020.

Research output: Contribution to journalArticleScientificpeer-review

Harvard

Deng, S, Jiang, Y, Li, H & Liu, Y 2020, 'Who contributes what? Scrutinizing the activity data of 4.2 million Zhihu users via immersion scores', INFORMATION PROCESSING AND MANAGEMENT, vol. 57, no. 5, 102274. https://doi.org/10.1016/j.ipm.2020.102274

APA

Vancouver

Author

Deng, Shengli ; Jiang, Yuting ; Li, Hongxiu ; Liu, Yong. / Who contributes what? Scrutinizing the activity data of 4.2 million Zhihu users via immersion scores. In: INFORMATION PROCESSING AND MANAGEMENT. 2020 ; Vol. 57, No. 5.

Bibtex - Download

@article{43520a1a2c0247d38792cd5ce9fe7c3b,
title = "Who contributes what? Scrutinizing the activity data of 4.2 million Zhihu users via immersion scores",
abstract = "Studies of knowledge communities have focused predominantly on contributors who ask questions and/or post replies, while little research has examined the contributions of those who neither pose questions nor suggest answers in knowledge communities. To illuminate member contributions of various sorts, this study evaluated user contribution to knowledge community from three dimensions (influence, content-contribution, and activeness) of immersion. Based on the user activity data of more than 4 million users from Zhihu, the largest online knowledge community in China, we calculated the immersion level for the four user groups (Lurkers, Questioners, Answerers, and Questioner-Answerers) in line with their question-asking and question-answering behaviors in Zhihu. The research findings revealed that Lurkers (members who posted nothing) showed higher community-immersion score than Questioners who asked questions only. The latter, Questioners, had the lowest community-immersion score, while Questioner-Answerers, who posted both questions and answers, exhibited the greatest contribution in the case knowledge community. We further made horizontal comparison of immersion score among the four different user groups, and found that when immersion scores of the four different user groups are above a certain threshold, the immersion scores of the four different user groups display a consistent distinguishing pattern. This result highlights the similarity of tendencies in behavioral orientation among different users in knowledge communities. Theoretical contributions and practical implications to be gleaned from this research are discussed.",
keywords = "Contribution, Immersion score, Knowledge community, SQA community, User engagement",
author = "Shengli Deng and Yuting Jiang and Hongxiu Li and Yong Liu",
year = "2020",
doi = "10.1016/j.ipm.2020.102274",
language = "English",
volume = "57",
journal = "INFORMATION PROCESSING AND MANAGEMENT",
issn = "0306-4573",
publisher = "Elsevier",
number = "5",

}

RIS (suitable for import to EndNote) - Download

TY - JOUR

T1 - Who contributes what? Scrutinizing the activity data of 4.2 million Zhihu users via immersion scores

AU - Deng, Shengli

AU - Jiang, Yuting

AU - Li, Hongxiu

AU - Liu, Yong

PY - 2020

Y1 - 2020

N2 - Studies of knowledge communities have focused predominantly on contributors who ask questions and/or post replies, while little research has examined the contributions of those who neither pose questions nor suggest answers in knowledge communities. To illuminate member contributions of various sorts, this study evaluated user contribution to knowledge community from three dimensions (influence, content-contribution, and activeness) of immersion. Based on the user activity data of more than 4 million users from Zhihu, the largest online knowledge community in China, we calculated the immersion level for the four user groups (Lurkers, Questioners, Answerers, and Questioner-Answerers) in line with their question-asking and question-answering behaviors in Zhihu. The research findings revealed that Lurkers (members who posted nothing) showed higher community-immersion score than Questioners who asked questions only. The latter, Questioners, had the lowest community-immersion score, while Questioner-Answerers, who posted both questions and answers, exhibited the greatest contribution in the case knowledge community. We further made horizontal comparison of immersion score among the four different user groups, and found that when immersion scores of the four different user groups are above a certain threshold, the immersion scores of the four different user groups display a consistent distinguishing pattern. This result highlights the similarity of tendencies in behavioral orientation among different users in knowledge communities. Theoretical contributions and practical implications to be gleaned from this research are discussed.

AB - Studies of knowledge communities have focused predominantly on contributors who ask questions and/or post replies, while little research has examined the contributions of those who neither pose questions nor suggest answers in knowledge communities. To illuminate member contributions of various sorts, this study evaluated user contribution to knowledge community from three dimensions (influence, content-contribution, and activeness) of immersion. Based on the user activity data of more than 4 million users from Zhihu, the largest online knowledge community in China, we calculated the immersion level for the four user groups (Lurkers, Questioners, Answerers, and Questioner-Answerers) in line with their question-asking and question-answering behaviors in Zhihu. The research findings revealed that Lurkers (members who posted nothing) showed higher community-immersion score than Questioners who asked questions only. The latter, Questioners, had the lowest community-immersion score, while Questioner-Answerers, who posted both questions and answers, exhibited the greatest contribution in the case knowledge community. We further made horizontal comparison of immersion score among the four different user groups, and found that when immersion scores of the four different user groups are above a certain threshold, the immersion scores of the four different user groups display a consistent distinguishing pattern. This result highlights the similarity of tendencies in behavioral orientation among different users in knowledge communities. Theoretical contributions and practical implications to be gleaned from this research are discussed.

KW - Contribution

KW - Immersion score

KW - Knowledge community

KW - SQA community

KW - User engagement

U2 - 10.1016/j.ipm.2020.102274

DO - 10.1016/j.ipm.2020.102274

M3 - Article

VL - 57

JO - INFORMATION PROCESSING AND MANAGEMENT

JF - INFORMATION PROCESSING AND MANAGEMENT

SN - 0306-4573

IS - 5

M1 - 102274

ER -