Opinion Mining on Social Media Data: Sentiment Analysis of User Preferences

Sustainability

Vasile-Daniel Păvăloaia¹  Doina Fotache¹  Magdalena Danileţ²  Elena-Mădălina Teodor³ 

[1] Department of Accounting, Business Information Systems and Statistics, Faculty of Economics and Business Administration, Alexandru Ioan Cuza University of Iasi, 700506 Iaşi, Romania;Department of Management, Marketing and Business Administration, Faculty of Economics and Business Administration, Alexandru Ioan Cuza University of Iasi, 700506 Iaşi, Romania;Web Department, Falcon Trading Company, 700521 Iaşi, Romania;

关键词: opinion mining;    social media;    social networks;    sentiment analysis;    sentiment polarity classification;   

DOI  :  10.3390/su11164459

来源: DOAJ

【 摘 要 】

Any brand’s presence on social networks has a significant impact on emotional reactions of its users to different types of posts on social media (SM). If a company understands the preferred types of posts (photo or video) of its customers, based on their reactions, it could make use of these preferences in designing its future communication strategy. The study examines how the use of SM technology and customer-centric management systems could contribute to sustainable business development of companies by means of social customer relationship management (sCRM). The two companies included in the study provide a general consumer good in the beverage industry. As such, it may be said that users interacting with the posts these companies make on their official channels are in fact customers or potential customers. The study aims to analyze customer reaction to two types of posts (photos or videos) on six social networks: Facebook, Twitter, Instagram, Pinterest, Google+ and Youtube. It brings evidence on the differences and similarities between the SM customer behaviors of two highly competitive brands in the beverage industry. Drawing on current literature on SM, sCRM and marketing, the output of this study is the conceptualization and measurement of a brand’s SM ability to understand customer preferences for different types of posts by using various statistical tools and the sentiment analysis (SA) technique applied to big sets of data.

【 授权许可】

Unknown