  Although, the fair amount of works in sentiment analysis (SA) and opinion
mining (OM) systems in the last decade and with respect to the performance of
these systems, but it still not desired performance, especially for
morphologically-Rich Language (MRL) such as Arabic, due to the complexities and
challenges exist in the nature of the languages itself. One of these challenges
is the detection of idioms or proverbs phrases within the writer text or
comment. An idiom or proverb is a form of speech or an expression that is
peculiar to itself. Grammatically, it cannot be understood from the individual
meanings of its elements and can yield different sentiment when treats as
separate words. Consequently, In order to facilitate the task of detection and
classification of lexical phrases for automated SA systems, this paper presents
AIPSeLEX a novel idioms/ proverbs sentiment lexicon for modern standard Arabic
(MSA) and colloquial. AIPSeLEX is manually collected and annotated at sentence
level with semantic orientation (positive or negative). The efforts of manually
building and annotating the lexicon are reported. Moreover, we build a
classifier that extracts idioms and proverbs, phrases from text using n-gram
and similarity measure methods. Finally, several experiments were carried out
on various data, including Arabic tweets and Arabic microblogs (hotel
reservation, product reviews, and TV program comments) from publicly available
Arabic online reviews websites (social media, blogs, forums, e-commerce web
sites) to evaluate the coverage and accuracy of AIPSeLEX.
