Open Access. Powered by Scholars. Published by Universities.®
Articles 1 - 2 of 2
Full-Text Articles in Business
Social Media Influencers And Instagram Storytelling: Case Study Of Singapore Instagram Influencers, Mark Chong, Gottipati Swapna
Social Media Influencers And Instagram Storytelling: Case Study Of Singapore Instagram Influencers, Mark Chong, Gottipati Swapna
Research Collection Lee Kong Chian School Of Business
While the use of social media influencers (SMIs) by brands is becoming more widespread, the academic literature about SMI communication is still scarce. This is one of the first studies on SMI brand storytelling, using data mining and natural language processing to understand how SMIs tell brand stories on Instagram, what kinds of stories they tell, and the impact they have on follower engagement. The findings show that the "rise-fall" emotional arc was the most common story arc used by SMIs. In addition, SMIs frequently used the first-person perspective and featured themselves as the protagonists in their stories. Last, SMIs …
Author Topic Model-Based Collaborative Filtering For Personalized Poi Recommendations, Shuhui Jiang, Xueming Qian, Jialie Shen, Yun Fu, Tao Mei
Author Topic Model-Based Collaborative Filtering For Personalized Poi Recommendations, Shuhui Jiang, Xueming Qian, Jialie Shen, Yun Fu, Tao Mei
Research Collection School Of Computing and Information Systems
From social media has emerged continuous needs for automatic travel recommendations. Collaborative filtering (CF) is the most well-known approach. However, existing approaches generally suffer from various weaknesses. For example, sparsity can significantly degrade the performance of traditional CF. If a user only visits very few locations, accurate similar user identification becomes very challenging due to lack of sufficient information for effective inference. Moreover, existing recommendation approaches often ignore rich user information like textual descriptions of photos which can reflect users' travel preferences. The topic model (TM) method is an effective way to solve the "sparsity problem," but is still far …