SAMAR: Subjectivity and sentiment analysis for Arabic social media
نویسندگان
چکیده
SAMAR: Subjectivity and sentiment analysis for Arabic social media Muhammad Abdul-Mageed a,b,∗, Mona Diab c, Sandra Kübler a a Department of Linguistics, Indiana University, 1021 E 3rd. St., Bloomington, IN 47405, USA b School of Library and Information Science, 1320 East 10th Street, Bloomington, IN 47405, USA c Department of Computer Science, School of Engineering & Applied Science, The George Washington University, Washington, DC, USA
منابع مشابه
SAMAR: A System for Subjectivity and Sentiment Analysis of Arabic Social Media
In this work, we present SAMAR, a system for Subjectivity and Sentiment Analysis (SSA) for Arabic social media genres. We investigate: how to best represent lexical information; whether standard features are useful; how to treat Arabic dialects; and, whether genre specific features have a measurable impact on performance. Our results suggest that we need individualized solutions for each domain...
متن کاملUsing Machine Learning Algorithms for Automatic Cyber Bullying Detection in Arabic Social Media
Social media allows people interact to express their thoughts or feelings about different subjects. However, some of users may write offensive twits to other via social media which known as cyber bullying. Successful prevention depends on automatically detecting malicious messages. Automatic detection of bullying in the text of social media by analyzing the text "twits" via one of the machine l...
متن کاملEvaluating Distant Supervision for Subjectivity and Sentiment Analysis on Arabic Twitter Feeds
Supervised machine learning methods for automatic subjectivity and sentiment analysis (SSA) are problematic when applied to social media, such as Twitter, since they do not generalise well to unseen topics. A possible remedy of this problem is to apply distant supervision (DS) approaches, which learn from large amounts of automatically annotated data. This research empirically evaluates the per...
متن کاملSubjectivity and Sentiment Annotation of Modern Standard Arabic Newswire
Subjectivity and sentiment analysis (SSA) is an area that has been witnessing a flurry of novel research. However, only few attempts have been made to build SSA systems for morphologically-rich languages (MRL). In the current study, we report efforts to partially bridge this gap. We present a newly labeled corpus of Modern Standard Arabic (MSA) from the news domain manually annotated for subjec...
متن کاملExploring Sentiment in Social Media: Bootstrapping Subjectivity Clues from Multilingual Twitter Streams
We study subjective language in social media and create Twitter-specific lexicons via bootstrapping sentiment-bearing terms from multilingual Twitter streams. Starting with a domain-independent, highprecision sentiment lexicon and a large pool of unlabeled data, we bootstrap Twitter-specific sentiment lexicons, using a small amount of labeled data to guide the process. Our experiments on Englis...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
عنوان ژورنال:
- Computer Speech & Language
دوره 28 شماره
صفحات -
تاریخ انتشار 2014