Sentiment Analysis of Twitter Data
Source abstract
Abstract
Twitter has become a major social media platform and has attracted considerable interest among researchers in sentiment analysis. Research into Twitter Sentiment Analysis (TSA) is an active subfield of text mining. TSA refers to the use of computers to process the subjective nature of Twitter data, including its opinions and sentiments. In this research, a thorough review of the most recent developments in this area, and a wide range of newly proposed algorithms and applications are explored. Each publication is arranged into a category based on its significance to a particular type of TSA method. The purpose of this survey is to provide a concise, nearly comprehensive overview of TSA techniques and related fields. The primary contributions of the survey are the detailed classifications of numerous recent articles and the depiction of the current direction of research in the field of TSA.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Sentiment Analysis and Opinion Mining · Advanced Text Analysis Techniques · Complex Network Analysis Techniques
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Engineering Research Center of Digital Forensics, Ministry of Education, Nanjing University of Information Science and Technology, Nanjing 210044, China
School of Computer Science, Nanjing University of Information Science and Technology, Nanjing 210044, China
College of Information and Communication Engineering, Sungkyunkwan University, Suwon 16419, Republic of Korea
Internet of Things & Smart City Innovation Platform, Zhuhai Fudan Innovation Institute, Zhuhai 519031, China
Funding
Research Startup Foundation of Nanjing University of Information Science & Technology · National Natural Science Foundation of China · Shandong Provincial Natural Science Foundation · China Postdoctoral Science Foundation
References (92)
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