Sentiment analysis is the process of using natural language processing, computational
linguistics, and other text analysis techniques to identify and extract subjective information in …

Opinion-mining or sentiment analysis continues to gain interest in industry and academics.
While there has been significant progress in developing models for sentiment analysis, the …

Abstract We present CAMeL Tools, a collection of open-source tools for Arabic natural
language processing in Python. CAMeL Tools currently provides utilities for pre-processing …

In this paper, we present Farasa, a fast and accurate Arabic segmenter. Our approach is
based on SVM-rank using linear kernels. We measure the performance of the segmenter in …

In recent years, online social networking has revolutionized interpersonal communication.
The newer research on language analysis in social media has been increasingly focusing …

SAMAR is a system for subjectivity and sentiment analysis (SSA) for Arabic social media
genres. Arabic is a morphologically rich language, which presents significant complexities …

Sentiment analysis research has predominantly been on English texts. Thus there exist
many sentiment resources for English, but less so for other languages. Approaches to …

As more and more Arabic textual information becomes available through the Web in homes
and businesses, via Internet and Intranet services, there is an urgent need for technologies …

Named entity recognition (NER) is the problem of locating and categorizing important nouns
and proper nouns in a text. In this chapter, we review the general state of research on entity …

When text is translated from one language into another, sentiment is preserved to varying
degrees. In this paper, we use Arabic social media posts as stand-in for source language …