lnu.sePublications
Change search
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf
Key Indicators for Data Sharing - In Relation with Digital Services
Daffodil International University, Bangladesh.
Daffodil International University, Bangladesh.
Linnaeus University, Faculty of Technology, Department of Media Technology. Telenor Grp, Oslo, Norway.
2016 (English)In: DATA MINING AND BIG DATA, DMBD 2016, Springer, 2016, p. 353-363Conference paper, Published paper (Refereed)
Abstract [en]

Rapid growth of data intensive digital services are creating potential risks of violating consumer centric data privacy. Protection of data privacy is becoming one of the key challenges for most of the big data business entities. Due to thank of big data, recommendation and personalization are becoming very popular in digital space. However it is hard to find a well-defined boundary which illustrates privacy threat to consumers' in relation with improving already opted-in communication services. In this paper, we initiated identifying key indicators for consumer configured privacy policy in relation with personalized services taking into consideration that "Privacy is a tool for balancing personalization". We survey user attitudes towards privacy and personalization and discovered key indicators for configuring privacy policy by analyzing survey data about privacy concern and data sharing attitude of the consumers. We found that consumers did not want to stop using social media based communication services due to privacy risks. Moreover, consumers have attitude of sharing their data, provided that appropriate personalization features are in place.

Place, publisher, year, edition, pages
Springer, 2016. p. 353-363
Series
Lecture Notes in Computer Science, ISSN 0302-9743 ; 9714
Keywords [en]
Data sharing, Big data driven digital services
National Category
Media and Communication Technology
Research subject
Computer and Information Sciences Computer Science, Media Technology
Identifiers
URN: urn:nbn:se:lnu:diva-58207DOI: 10.1007/978-3-319-40973-3_35ISI: 000386323800035ISBN: 978-3-319-40973-3 (print)ISBN: 978-3-319-40972-6 (print)OAI: oai:DiVA.org:lnu-58207DiVA, id: diva2:1047734
Conference
1st International Conference on Data Mining and Big Data (DMBD), JUN 25-30, 2016, Bali, INDONESIA
Available from: 2016-11-18 Created: 2016-11-18 Last updated: 2018-01-13Bibliographically approved

Open Access in DiVA

No full text in DiVA

Other links

Publisher's full text

Authority records BETA

Rana, Juwel

Search in DiVA

By author/editor
Rana, Juwel
By organisation
Department of Media Technology
Media and Communication Technology

Search outside of DiVA

GoogleGoogle Scholar

doi
isbn
urn-nbn

Altmetric score

doi
isbn
urn-nbn
Total: 51 hits
CiteExportLink to record
Permanent link

Direct link
Cite
Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
  • rtf