It is becoming increasingly difficult to know who is working on what and how in
computational studies of Dialectal Arabic. This study comes to chart the field by conducting a …

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 …

This book provides system developers and researchers in natural language processing and
computational linguistics with the necessary background information for working with the …

The written form of the Arabic language, Modern Standard Arabic (MSA), differs in a non-
trivial manner from the various spoken regional dialects of Arabic—the true “native …

Social media platforms such as blogs, social networking sites, content communities and
virtual worlds are tremendously becoming one of the most powerful sources for news …

Arabic Dialects present many challenges for machine translation, not least of which is the
lack of data resources. We use crowdsourcing to cheaply and quickly build Levantine …

In this paper, we offer broad insight into the underperformance of Arabic constituency
parsing by analyzing the interplay of linguistic phenomena, annotation choices, and model …

The daily spoken variety of Arabic is often termed the colloquial or dialect form of Arabic.
There are many Arabic dialects across the Arab World and within other Arabic speaking …

We present in this paper PADIC, a Parallel Arabic DIalect Corpus we built from scratch, then
we conducted experiments on crossdialect Arabic machine translation. PADIC is composed …

The many differences between Dialectal Arabic and Modern Standard Arabic (MSA) pose a
challenge to the majority of Arabic natural language processing tools, which are designed …