Open Access. Powered by Scholars. Published by Universities.®
- Institution
- Publication
- Publication Type
Articles 1 - 6 of 6
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 …
Prediction And Recommendations On The It Leaners' Learning Path As A Collective Intelligence Using A Data Mining Technique, Seong-Yong Hong, Juyun Cho, Yonghyun Hwang
Prediction And Recommendations On The It Leaners' Learning Path As A Collective Intelligence Using A Data Mining Technique, Seong-Yong Hong, Juyun Cho, Yonghyun Hwang
Journal of International Technology and Information Management
With the recent advances in computer technology along with pervasive internet accesses, data analytics is getting more attention than ever before. In addition, research areas on data analysis are diverging and integrating lots of different fields such as a business and social sector. Especially, recent researches focus on the data analysis for a better intelligent decision making and prediction system. This paper analyzes data collected from current IT learners who have already studied various IT subjects to find the IT learners’ learning patterns. The most popular learning patterns are identified through an association rule data mining using an arules package …
Evaluation Of Classification And Ensemble Algorithms For Bank Customer Marketing Response Prediction, Olatunji Apampa
Evaluation Of Classification And Ensemble Algorithms For Bank Customer Marketing Response Prediction, Olatunji Apampa
Journal of International Technology and Information Management
This article attempts to improve the performance of classification algorithms used in the bank customer marketing response prediction of an unnamed Portuguese bank using the Random Forest ensemble. A thorough exploratory data analysis (EDA) was conducted on the data in order to ascertain the presence of anomalies such as outliers and extreme values. The EDA revealed that the bank data had 45, 211 instances and 17 features, with 11.7% positive responses. This was in addition to the detection of outliers and extreme values. Classification algorithms used for modelling the bank dataset include; Logistic Regression, Decision Tree, Naïve Bayes and the …
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 …
Data Mining The Harness Track And Predicting Outcomes, Robert P. Schumaker
Data Mining The Harness Track And Predicting Outcomes, Robert P. Schumaker
Journal of International Technology and Information Management
This paper presented the S&C Racing system that uses Support Vector Regression (SVR) to predict harness race finishes and analyzed it on fifteen months of data from Northfield Park. We found that our system outperforms the most common betting strategies of wagering on the favorites and the mathematical arbitrage Dr. Z system in five of the seven wager types tested. This work would suggest that an informational inequality exists within the harness racing market that is not apparent to domain experts.
Privacy Law And The Internet Using Facebook.Com As A Case Study, Amelia D. Grubbs
Privacy Law And The Internet Using Facebook.Com As A Case Study, Amelia D. Grubbs
Chancellor’s Honors Program Projects
No abstract provided.