Discovering user attitudes of business in Twitter language feed

العناوين الأخرى

فهم و اكتشاف توجهات المستخدمين العرب لتويتر و ربطها مع الأونتولوجي

مقدم أطروحة جامعية

Abd al-Nabi, Ibrahim Muhammad

مشرف أطروحة جامعية

Tartir, Samir

أعضاء اللجنة

Hanna, Samir S.
Hadi, Wail

الجامعة

جامعة فيلادلفيا

الكلية

كلية تكنولوجيا المعلومات

القسم الأكاديمي

قسم علم الحاسوب

دولة الجامعة

الأردن

الدرجة العلمية

ماجستير

تاريخ الدرجة العلمية

2013

الملخص الإنجليزي

-Research done on Arabic sentiment analysis is considered very limited almost in its early steps compared to other languages like English whether at business level or social level.

Twitter now can be considered as an information network instead of a social network; this is because Twitter is a platform for shared experiences and it is a very human network .Twitter, a micro-blogging service, has emerged as a new medium in spotlight through recent happenings.

Sentiment analysis aims to determine the attitude of a speaker or a writer with respect to some topic or the overall contextual polarity of a document.

The attitude may be his or her judgment or evaluation.

Thesis problems are discovering user attitudes and business insights from Arabic Twitter feed and Enhancing Arabic Natural Language Processing using novel Semantic Web techniques The Motivation for our work is Social media have swept into every industry and business function and are now an important factor of production, The primary goal of our work is to help companies make better business decisions by enabling semantic web and data mining.

We proposes a new model to discover Arabic business insights from tweets that may affect the decision making process, This model classifies Arabic tweets into positive and negative and tries to enhance the classification precision of tweets by creating Arabic Sentiment Ontology (ASO) for first time and also building our ASO aggregate weights algorithm.

Our Solution will be a starting point for any research that focus on Arabic sentiment analysis and extract information from Arabic social media.

التخصصات الرئيسية

تكنولوجيا المعلومات وعلم الحاسوب

الموضوعات

• مواقع التواصل الاجتماعي
• الأردن
• الإنترنت
• الجوانب الاجتماعية

عدد الصفحات

50

قائمة المحتويات

• APA
• MLA
• AMA

لغة النص

الإنجليزية

نوع البيانات

رسائل جامعية

رقم السجل

BIM-546125