Opinion Mining Using Live Twitter Data

被引：1

作者：

Aslam, Andleeb ^{[1
]}

Qamar, Usman ^{[1
]}

Khan, Reda Ayesha ^{[1
]}

Saqib, Pakizah ^{[1
]}

Ahmad, Aleena ^{[1
]}

Qadeer, Aiman ^{[1
]}

机构：

[1] NUST, CEME, Dept Comp & Software Engn, Islamabad, Pakistan

来源：

2019 22ND IEEE INTERNATIONAL CONFERENCE ON COMPUTATIONAL SCIENCE AND ENGINEERING (IEEE CSE 2019) AND 17TH IEEE INTERNATIONAL CONFERENCE ON EMBEDDED AND UBIQUITOUS COMPUTING (IEEE EUC 2019) | 2019年

关键词：

component; Twitter; Opinion Mining; Sentiment Analysis; Twitter Data; Polarity;

D O I：

10.1109/CSE/EUC.2019.00016

中图分类号：

TP301 [理论、方法];

学科分类号：

081202 ;

摘要：

Opinion mining and extracting Sentiments of people is the need of today. This is the era of Big data. Because of social networking sites, it's easy to analyze sentiments of people. Sentiment analysis is a technique to extract opinions of people regarding any product, issue or personality. This paper is about extracting live twitter data regarding any topic and converting it into structured form from unstructured one. Opinions are extracted from the text data and polarity is assigned against each tweet. Polarity of data can be positive, negative or neutral. Most recent and popular opinions can be extracted. It is useful for both market analyzers as well as customers. Customers get to know honest reviews about any product and companies can know their customer's interests. Furthermore, predictions are also given based on the classified data.

引用

页码：36 / 39

页数：4

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