Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis

Nicolae Nistor; Mihai Dascălu; Lucia Larise Stavarache; Christian Tarnai; Stefan Trausan-Matu

doi:10.1007/978-981-287-868-7_2

Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis

Nicolae Nistor, Mihai Dascălu, Lucia Larise Stavarache, Christian Tarnai, Stefan Trausan-Matu

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

37 Downloads (Pure)

Abstract

Using online knowledge communities (OKCs) from the Internet as informal learning environments poses the question how likely these communities will be to integrate learners as new members. Such prediction is the purpose of the current study. Based on the approaches of voices interanimation and polyphony, a natural language processing tool was employed for dialog analysis in integrative versus non-integrative blog-based OKCs. Four dialog dimensions were identified: participants’ long-term persistence in the discourse, the community response to their participation, their communicative centrality, and their communicative peripherality. Hierarchical clusters built upon these dimensions reflect socio-cognitive structures including central, regular, and peripheral OKC members. While the socio-cognitive structures did not make a significant difference, integrative OKCs display significantly stronger peripherality, community response, and centrality as compared to non-integrative OKCs.

Original language	English
Title of host publication	State-of-the-Art and Future Directions of Smart Learning
Editors	Yanyan Li, Maiga Chang, Milos Kravcik, Elvira Popescu, Ronghuai Huang, Kinshuk, Nian-Shing Chen
Publisher	Springer Singapore
Chapter	2
Pages	13-17
Edition	1
ISBN (Electronic)	978-981-287-868-7
ISBN (Print)	978-981-287-866-3, 978-981-10-1313-3
DOIs	https://doi.org/10.1007/978-981-287-868-7_2
Publication status	Published - 27 Oct 2015
Externally published	Yes

Publication series

Series	Lecture Notes in Educational Technology
ISSN	2196-4963

Keywords

knowledge communities
newcomer integration
dialog analysis
social learning analytics

Access to Document

10.1007/978-981-287-868-7_2Licence: Unspecified

Nic ICSLE 2015Final published version, 226 KBLicence: CC BY-NC-SA

https://tinyurl.com/ycfbrfbwLicence: CC BY-NC-SA

Rage: Realising an Applied Gaming Eco-system
Westera, W. (PI), Georgiadis, K. (CoI), Saveski, G. (CoI), van Lankveld, G. (CoI), Bahreini, K. (CoI), van der Vegt, W. (CoI), Berkhout, J. (CoI), Nyamsuren, E. (CoI), Kluijfhout, E. (CoI) & Nadolski, R. (CoI)
European Union
1/02/15 → 31/07/19
Project: Research

Cite this

Nistor, N., Dascălu, M., Stavarache, L. L., Tarnai, C., & Trausan-Matu, S. (2015). Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis. In Y. Li, M. Chang, M. Kravcik, E. Popescu, R. Huang, Kinshuk, & N.-S. Chen (Eds.), State-of-the-Art and Future Directions of Smart Learning (1 ed., pp. 13-17). Springer Singapore. https://doi.org/10.1007/978-981-287-868-7_2

Nistor, Nicolae ; Dascălu, Mihai ; Stavarache, Lucia Larise et al. / Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis. State-of-the-Art and Future Directions of Smart Learning. editor / Yanyan Li ; Maiga Chang ; Milos Kravcik ; Elvira Popescu ; Ronghuai Huang ; Kinshuk ; Nian-Shing Chen. 1. ed. Springer Singapore, 2015. pp. 13-17 (Lecture Notes in Educational Technology).

@inbook{d87a6f8259f141299d2218dbab993995,

title = "Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis",

abstract = "Using online knowledge communities (OKCs) from the Internet as informal learning environments poses the question how likely these communities will be to integrate learners as new members. Such prediction is the purpose of the current study. Based on the approaches of voices interanimation and polyphony, a natural language processing tool was employed for dialog analysis in integrative versus non-integrative blog-based OKCs. Four dialog dimensions were identified: participants{\textquoteright} long-term persistence in the discourse, the community response to their participation, their communicative centrality, and their communicative peripherality. Hierarchical clusters built upon these dimensions reflect socio-cognitive structures including central, regular, and peripheral OKC members. While the socio-cognitive structures did not make a significant difference, integrative OKCs display significantly stronger peripherality, community response, and centrality as compared to non-integrative OKCs.",

keywords = "knowledge communities, newcomer integration, dialog analysis, social learning analytics",

author = "Nicolae Nistor and Mihai Dasc{\u a}lu and Stavarache, {Lucia Larise} and Christian Tarnai and Stefan Trausan-Matu",

year = "2015",

month = oct,

day = "27",

doi = "10.1007/978-981-287-868-7_2",

language = "English",

isbn = "978-981-287-866-3",

series = "Lecture Notes in Educational Technology",

publisher = "Springer Singapore",

pages = "13--17",

editor = "Yanyan Li and Maiga Chang and Milos Kravcik and Elvira Popescu and Huang, {Ronghuai } and Kinshuk and Nian-Shing Chen",

booktitle = "State-of-the-Art and Future Directions of Smart Learning",

address = "Singapore",

edition = "1",

}

Nistor, N, Dascălu, M, Stavarache, LL, Tarnai, C & Trausan-Matu, S 2015, Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis. in Y Li, M Chang, M Kravcik, E Popescu, R Huang, Kinshuk & N-S Chen (eds), State-of-the-Art and Future Directions of Smart Learning. 1 edn, Springer Singapore, Lecture Notes in Educational Technology, pp. 13-17. https://doi.org/10.1007/978-981-287-868-7_2

Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis. / Nistor, Nicolae; Dascălu, Mihai; Stavarache, Lucia Larise et al.
State-of-the-Art and Future Directions of Smart Learning. ed. / Yanyan Li; Maiga Chang; Milos Kravcik; Elvira Popescu; Ronghuai Huang; Kinshuk; Nian-Shing Chen. 1. ed. Springer Singapore, 2015. p. 13-17 (Lecture Notes in Educational Technology).

Research output: Chapter in Book/Report/Conference proceeding › Chapter › Academic › peer-review

TY - CHAP

T1 - Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis

AU - Nistor, Nicolae

AU - Dascălu, Mihai

AU - Stavarache, Lucia Larise

AU - Tarnai, Christian

AU - Trausan-Matu, Stefan

PY - 2015/10/27

Y1 - 2015/10/27

N2 - Using online knowledge communities (OKCs) from the Internet as informal learning environments poses the question how likely these communities will be to integrate learners as new members. Such prediction is the purpose of the current study. Based on the approaches of voices interanimation and polyphony, a natural language processing tool was employed for dialog analysis in integrative versus non-integrative blog-based OKCs. Four dialog dimensions were identified: participants’ long-term persistence in the discourse, the community response to their participation, their communicative centrality, and their communicative peripherality. Hierarchical clusters built upon these dimensions reflect socio-cognitive structures including central, regular, and peripheral OKC members. While the socio-cognitive structures did not make a significant difference, integrative OKCs display significantly stronger peripherality, community response, and centrality as compared to non-integrative OKCs.

AB - Using online knowledge communities (OKCs) from the Internet as informal learning environments poses the question how likely these communities will be to integrate learners as new members. Such prediction is the purpose of the current study. Based on the approaches of voices interanimation and polyphony, a natural language processing tool was employed for dialog analysis in integrative versus non-integrative blog-based OKCs. Four dialog dimensions were identified: participants’ long-term persistence in the discourse, the community response to their participation, their communicative centrality, and their communicative peripherality. Hierarchical clusters built upon these dimensions reflect socio-cognitive structures including central, regular, and peripheral OKC members. While the socio-cognitive structures did not make a significant difference, integrative OKCs display significantly stronger peripherality, community response, and centrality as compared to non-integrative OKCs.

KW - knowledge communities

KW - newcomer integration

KW - dialog analysis

KW - social learning analytics

U2 - 10.1007/978-981-287-868-7_2

DO - 10.1007/978-981-287-868-7_2

M3 - Chapter

SN - 978-981-287-866-3

SN - 978-981-10-1313-3

T3 - Lecture Notes in Educational Technology

SP - 13

EP - 17

BT - State-of-the-Art and Future Directions of Smart Learning

A2 - Li, Yanyan

A2 - Chang, Maiga

A2 - Kravcik, Milos

A2 - Popescu, Elvira

A2 - Huang, Ronghuai

A2 - Kinshuk,

A2 - Chen, Nian-Shing

PB - Springer Singapore

ER -

Nistor N, Dascălu M, Stavarache LL, Tarnai C, Trausan-Matu S. Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis. In Li Y, Chang M, Kravcik M, Popescu E, Huang R, Kinshuk, Chen NS, editors, State-of-the-Art and Future Directions of Smart Learning. 1 ed. Springer Singapore. 2015. p. 13-17. (Lecture Notes in Educational Technology). doi: 10.1007/978-981-287-868-7_2

Predicting Newcomer Integration in Online Knowledge Communities by Automated Dialog Analysis

Abstract

Publication series

Keywords

Access to Document

Fingerprint

Projects

Rage: Realising an Applied Gaming Eco-system

Cite this