Word clustering based on POS feature for efficient twitter sentiment analysis
نویسندگان
چکیده
منابع مشابه
A High-Performance Model based on Ensembles for Twitter Sentiment Classification
Background and Objectives: Twitter Sentiment Classification is one of the most popular fields in information retrieval and text mining. Millions of people of the world intensity use social networks like Twitter. It supports users to publish tweets to tell what they are thinking about topics. There are numerous web sites built on the Internet presenting Twitter. The user can enter a sentiment ta...
متن کاملEntity Based Sentiment Analysis on Twitter
Its fair to say that when it comes to global entities that matter to us, we are quite obsessed with finding out what other people think about them. In the past, querying people’s opinions with respect to a global entity such as Michael Jackson, Microsoft or Cuba was done through user polls funded by organizations and only a small percentage of these questionable polls trickled to the average pe...
متن کاملSentiment Analysis on Twitter
With the rise of social networking epoch, there has been a surge of user generated content. Microblogging sites have millions of people sharing their thoughts daily because of its characteristic short and simple manner of expression. We propose and investigate a paradigm to mine the sentiment from a popular real-time microblogging service, Twitter, where users post real time reactions to and op...
متن کاملEfficient Method Based on Combination of Deep Learning Models for Sentiment Analysis of Text
People's opinions about a specific concept are considered as one of the most important textual data that are available on the web. However, finding and monitoring web pages containing these comments and extracting valuable information from them is very difficult. In this regard, developing automatic sentiment analysis systems that can extract opinions and express their intellectual process has ...
متن کاملLearning Sentiment-Specific Word Embedding for Twitter Sentiment Classification
We present a method that learns word embedding for Twitter sentiment classification in this paper. Most existing algorithms for learning continuous word representations typically only model the syntactic context of words but ignore the sentiment of text. This is problematic for sentiment analysis as they usually map words with similar syntactic context but opposite sentiment polarity, such as g...
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: Human-centric Computing and Information Sciences
سال: 2018
ISSN: 2192-1962
DOI: 10.1186/s13673-018-0140-y