Affiliations: [a] School of Economy and Management, Hubei University of Technology, Wuhan 430064, Hubei, China | [b] School of Management, Wuhan University of Technology, Wuhan 430072, Hubei, China | [c] School of Electrical Engineering and Computer Science, Queensland University of Technology (QUT), Australia, Brisbane, QLD 4001
Abstract: This article summarizes the research methods for processing short texts in the microblog, one of the most popular social media sites, analyzes the bottleneck problems and challenging issues, and discusses the possible direction and strategies for solving the above problems. Comprehensive literature review on short text processing has also been conducted by the way of case tracking and case studies. Text categorization and text clustering are the main research methods for processing short texts in microblogs, and topic detection, sentiment analysis, smart healthcare, business intelligence and location services are hot topics for the application of these methods. We also found some challenges for processing microblog short texts, including semantic processing, noise reduction, clarification of fuzzy themes and handling big data. The real-time online processing of big data is expected to be the main research direction in the future.
Keywords: Microblog, short text, text classification, text clustering, sentiment analysis, topic detection
