Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Sentiment Analysis of Arabic Tweets: Feature Engineering and A Hybrid
  Approach   Sentiment Analysis in Arabic is a challenging task due to the rich morphology
of the language. Moreover, the task is further complicated when applied to
Twitter data that is known to be highly informal and noisy. In this paper, we
develop a hybrid method for sentiment analysis for Arabic tweets for a specific
Arabic dialect which is the Saudi Dialect. Several features were engineered and
evaluated using a feature backward selection method. Then a hybrid method that
combines a corpus-based and lexicon-based method was developed for several
classification models (two-way, three-way, four-way). The best F1-score for
each of these models was (69.9,61.63,55.07) respectively.

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The categories of this paper are: hep-ph
24
The categories of this paper are: dg-ga
31
The categories of this paper are: ao-sci
25
The categories of this paper are: patt-sol
15
The categories of this paper are: nucl-ex
9
The categories of this paper are: nlin
34
The categories of this paper are: chem-ph
5
The categories of this paper are: gr-qc
28
The categories of this paper are: alg-geom
10
The categories of this paper are: q-bio
35
The categories of this paper are: mtrl-th
3
The categories of this paper are: physics
37
The categories of this paper are: supr-con
21
The categories of this paper are: adap-org
16
The categories of this paper are: stat
7
The categories of this paper are: hep-th