Lexicon-Based Methods for Sentiment Analysis

نویسندگان

  • Maite Taboada
  • Julian Brooke
  • Milan Tofiloski
  • Kimberly D. Voll
  • Manfred Stede
چکیده

We present a lexicon-based approach to extracting sentiment from text. The Semantic Orientation CALculator (SO-CAL) uses dictionaries of words annotated with their semantic orientation (polarity and strength), and incorporates intensification and negation. SO-CAL is applied to the polarity classification task, the process of assigning a positive or negative label to a text that captures the text’s opinion towards its main subject matter. We show that SO-CAL’s performance is consistent across domains and in completely unseen data. Additionally, we describe the process of dictionary creation, and our use of Mechanical Turk to check dictionaries for consistency and reliability.

برای دانلود رایگان متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

A Supervised Method for Constructing Sentiment Lexicon in Persian Language

Due to the increasing growth of digital content on the internet and social media, sentiment analysis problem is one of the emerging fields. This problem deals with information extraction and knowledge discovery from textual data using natural language processing has attracted the attention of many researchers. Construction of sentiment lexicon as a valuable language resource is a one of the imp...

متن کامل

یک چارچوب نیمه‌نظارتی مبتنی بر لغت‌نامه وفقی خودساخت جهت تحلیل نظرات فارسی

With the appearance of Web 2.0 and 3.0, users’ contribution to WWW has created a huge amount of valuable expressed opinions. Considering the difficulty or impossibility of manually analyzing such big data, sentiment analysis, as a branch of natural language processing, has been highly considered. Despite the other (popular) languages, a limited number of research studies have been conducted in ...

متن کامل

Context-Sensitive Lexicon Features for Neural Sentiment Analysis

Sentiment lexicons have been leveraged as a useful source of features for sentiment analysis models, leading to the state-of-the-art accuracies. On the other hand, most existing methods use sentiment lexicons without considering context, typically taking the count, sum of strength, or maximum sentiment scores over the whole input. We propose a context-sensitive lexicon-based method based on a s...

متن کامل

Sentiment Lexicon Construction with Representation Learning Based on Hierarchical Sentiment Supervision

Sentiment lexicon is an important tool for identifying the sentiment polarity of words and texts. How to automatically construct sentiment lexicons has become a research topic in the field of sentiment analysis and opinion mining. Recently there were some attempts to employ representation learning algorithms to construct a sentiment lexicon with sentiment-aware word embedding. However, these me...

متن کامل

Discovering the Discriminative Views: Measuring Term Weights for Sentiment Analysis

This paper describes an approach to utilizing term weights for sentiment analysis tasks and shows how various term weighting schemes improve the performance of sentiment analysis systems. Previously, sentiment analysis was mostly studied under data-driven and lexicon-based frameworks. Such work generally exploits textual features for fact-based analysis tasks or lexical indicators from a sentim...

متن کامل

Sentiment Analysis with Automatically Constructed Lexicon and Three-Way Decision

An unsupervised sentiment analysis method is presented to classify user comments on laptops into positive ones and negative ones. The method automatically extracts informative features in testing dataset and labels the sentiment polarity of each feature to make a domainspecific lexicon. The classification accuracy of this lexicon will be compared to that with an existing general sentiment lexic...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

عنوان ژورنال:
  • Computational Linguistics

دوره 37  شماره 

صفحات  -

تاریخ انتشار 2011