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Cited 9 time in webofscience Cited 21 time in scopus
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Understanding Customer Experience Diffusion on Social Networking Services by Big Data Analytics

Authors
Piccialli, FrancescoJung, Jai E.
Issue Date
Aug-2017
Publisher
SPRINGER
Keywords
Business intelligence; Social big data; Information diffusion; Content-based Analytics; Social media
Citation
MOBILE NETWORKS & APPLICATIONS, v.22, no.4, pp 605 - 612
Pages
8
Journal Title
MOBILE NETWORKS & APPLICATIONS
Volume
22
Number
4
Start Page
605
End Page
612
URI
https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/4159
DOI
10.1007/s11036-016-0803-8
ISSN
1383-469X
1572-8153
Abstract
Social networking services (e.g., Facebook and Twitter) are playing a significant role of interacting with customers. In particular, most of businesses are trying to exploit such social networking services for more profit, since it has dramatically become an information carrier for customers who are disseminating latest information about products and services. Thus, this study examines how information shared by companies is distributed and what the important factors in understanding information dissemination are. More importantly, this study classifies the types of tweets posted by a company and then to investigate the effect of these types of tweets on diffusion. By using content analysis, this study defined three types, which are i) information provision (IF), ii) advertisement (AD), and iii) both (IFAD), with 8 specific concepts. These results indicate that the differences are significant for all three types of information content. It shows that companies can spread information more quickly by providing the IFAD type rather than the AD type.
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소프트웨어대학 (소프트웨어학부)
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