Ghada  Hafez, Rasha  Ismail, Omar  Karam, 
    Opinion Mining with Aspects and Shortcuts for Prediction Model,
    Asian Journal of Information Technology,
    Volume 17,Issue 3,
    2018,
    Pages 212-217,
    ISSN 1682-3915,
    ajit.2018.212.217,
    (https://makhillpublications.co/view-article.php?doi=ajit.2018.212.217)
    Abstract: Opinion mining or sentiment analysis extract specified information from a large amount of text or reviews given by the internet users. Opinion mining classifies the large text of opinions as positive (good), negative (bad) or neutral. According to the number of positive, negative and neutral reviews, the product or service will be rated. Most researches neglected the shortcuts of words like (CD “Compact Disc”), (GR8 “means Great”). To avoid classify these words wrong, a database is built for some of these shortcuts with its meaning and orientation (positive, negative or neutral). Also, few researches tried to extract tempo words from text as general not from opinions, so that, a framework is proposed to merge tempo and sentiment analysis to enhance the prediction for the opinions.
    Keywords: Aspect mining;opinion mining;tempo wrods;text mining;shortcuts;database