Predictive Analysis on Twitter: Techniques and Applications

Ugur Kursuncu; Manas Gaur; Usha Lokala; Krishnaprasad Thirunarayan; Amit Sheth; Budak Arpinar

doi:10.1007/978-3-319-94105-9

Predictive Analysis on Twitter: Techniques and Applications

Ugur Kursuncu, Manas Gaur, Usha Lokala, Krishnaprasad Thirunarayan, Amit Sheth, Budak Arpinar

Wright State University

Research output: Chapter in Book/Report/Conference proceeding › Chapter

Abstract

Predictive analysis of social media data has attracted considerable attention from the research community as well as the business world because of the essential and actionable information it can provide. Over the years, extensive experimentation and analysis for insights have been carried out using Twitter data in various domains such as healthcare, public health, politics, social sciences, and demographics. In this chapter, we discuss techniques, approaches, and state-of-the-art applications of predictive analysis of Twitter data. Specifically, we present fine-grained analysis involving aspects such as sentiment, emotion, and the use of domain knowledge in the coarse-grained analysis of Twitter data for making decisions and taking actions, and relate a few success stories.

Original language	American English
Title of host publication	Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining
DOIs	https://doi.org/10.1007/978-3-319-94105-9
State	Published - Jan 1 2018

Disciplines

Bioinformatics
Communication
Communication Technology and New Media
Computer Sciences
Databases and Information Systems
Life Sciences
OS and Networks
Physical Sciences and Mathematics
Science and Technology Studies
Social and Behavioral Sciences

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https://doi.org/10.1007/978-3-319-94105-9

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AU - Kursuncu, Ugur

AU - Gaur, Manas

AU - Lokala, Usha

AU - Thirunarayan, Krishnaprasad

AU - Sheth, Amit

AU - Arpinar, Budak

PY - 2018/1/1

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AB - Predictive analysis of social media data has attracted considerable attention from the research community as well as the business world because of the essential and actionable information it can provide. Over the years, extensive experimentation and analysis for insights have been carried out using Twitter data in various domains such as healthcare, public health, politics, social sciences, and demographics. In this chapter, we discuss techniques, approaches, and state-of-the-art applications of predictive analysis of Twitter data. Specifically, we present fine-grained analysis involving aspects such as sentiment, emotion, and the use of domain knowledge in the coarse-grained analysis of Twitter data for making decisions and taking actions, and relate a few success stories.

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M3 - Chapter

BT - Emerging Research Challenges and Opportunities in Computational Social Network Analysis and Mining

ER -

Predictive Analysis on Twitter: Techniques and Applications

Abstract

Disciplines

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