Sentiment Analysis on Twitter Data using KNN and SVM
نویسندگان
چکیده
منابع مشابه
Sentiment Analysis on Twitter Data using KNN and SVM
Millions of users share opinions on various topics using micro-blogging every day. Twitter is a very popular microblogging site where users are allowed a limit of 140 characters; this kind of restriction makes the users be concise as well as expressive at the same time. For that reason, it becomes a rich source for sentiment analysis and belief mining. The aim of this paper is to develop such a...
متن کامل2016 Olympic Games on Twitter: Sentiment Analysis of Sports Fans Tweets using Big Data Framework
Big data analytics is one of the most important subjects in computer science. Today, due to the increasing expansion of Web technology, a large amount of data is available to researchers. Extracting information from these data is one of the requirements for many organizations and business centers. In recent years, the massive amount of Twitter's social networking data has become a platform for ...
متن کاملSentiment Analysis on Twitter Data
Sentiment analysis is a type of natural language processing for tracking the mood of the public about a particular product or topic. Sentiment analysis, which is also called opinion mining, involves in building a system to collect and examine opinions about the product made in blog posts, comments, reviews or tweets. Sentiment analysis can be useful in several ways. In fact, it has spread from ...
متن کاملForecasting Stock Price Movements Based on Opinion Mining and Sentiment Analysis: An Application of Support Vector Machine and Twitter Data
Today, social networks are fast and dynamic communication intermediaries that are a vital business tool. This study aims at examining the views of those involved with Facebook stocks so that we can summarize their views to predict the general behavior of this stock and collectively consider possible Facebook stock price movements, and create a more accurate pattern compared to previous patterns...
متن کاملKUNLPLab: Sentiment Analysis on Twitter Data
This paper presents the system submitted by KUNLPLab for SemEval-2014 Task9 Subtask B: Message Polarity on Twitter data. Lexicon features and bag-of-words features are mainly used to represent the datasets. We trained a logistic regression classifier and got an accuracy of 6% increase from the baseline feature representation. The effect of pre-processing on the classifier’s accuracy is also dis...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: International Journal of Advanced Computer Science and Applications
سال: 2017
ISSN: 2156-5570,2158-107X
DOI: 10.14569/ijacsa.2017.080603