Understanding Customer Experience Diffusion on Social Networking Services by Big Data Analytics

• Published in: Mobile networks and applications Vol. 22; no. 4; pp. 605 - 612
• Main Authors: Piccialli, Francesco, Jung, Jai E.
• Format: Journal Article
• Language: English
• Published: New York Springer US 01.08.2017; Springer Nature B.V
• Subjects: Advertisements; Analytics; Communications Engineering; Computer Communication Networks; Content analysis; Customer satisfaction; Customer services; Customers; Data management; Electrical Engineering; Engineering; Information dissemination; IT in Business; Network directories; Networks; Social networks; Social big data; Business intelligence; Information diffusion; Content-based Analytics; Social media
• ISSN: 1383-469X; 1572-8153
• DOI: 10.1007/s11036-016-0803-8

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.