Social media has become an integral part of everyday human life and as a result, social media platforms such as Twitter have been widely adopted by businesses for commercial purposes. Due to the huge popularity of social media platforms, there is an ever increasing pool of user generated content, Big Social Data (BSD), publicly available for businesses to analyze. However, there is limited amount of research done on the smartphone industry Twitter usage that seeks to establish a more consistent social media strategy and understand consumer behaviour. In order to fully leverage BSD, businesses need not only to analyze user generated content on their own channels but also extend the analysis to competitors channels to truly understand the trends in the industry and best practices. This paper is an attempt to turn Twitter data from sites of five major smartphone manufacturers into knowledge about trends in the industry that can potentially inform the strategic decision making of social media managers and other relevant stakeholders. In order to derive insights we employ concepts of interaction analysis, machine learning-based conversation analysis and visual analytics. The results show that there is a lack of clear strategy in the industry. However, we could identify strategies that overperform those of competitors. We discovered that high levels of engagement with consumers potentially increases the users activity levels and positively impacts the polarity of opinion. We also demonstrated that text analytics can be leveraged to produce insights about consumers preferences and reveal dominant topics of discussion. Such insights can ultimately be a resource in product and service development as well as information for shaping the social media strategy.
|Educations||MSc in Business Administration and E-business, (Graduate Programme) Final Thesis|
|Number of pages||98|