<?xml version="1.0" encoding="ISO-8859-1"?><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" xmlns:xsi="http://www.w3.org/2001/XMLSchema-instance">
<front>
<journal-meta>
<journal-id>1405-5546</journal-id>
<journal-title><![CDATA[Computación y Sistemas]]></journal-title>
<abbrev-journal-title><![CDATA[Comp. y Sist.]]></abbrev-journal-title>
<issn>1405-5546</issn>
<publisher>
<publisher-name><![CDATA[Instituto Politécnico Nacional, Centro de Investigación en Computación]]></publisher-name>
</publisher>
</journal-meta>
<article-meta>
<article-id>S1405-55462018000300777</article-id>
<article-id pub-id-type="doi">10.13053/cys-22-3-3031</article-id>
<title-group>
<article-title xml:lang="en"><![CDATA[Using Tweets and Emojis to Build TEAD: an Arabic Dataset for Sentiment Analysis]]></article-title>
</title-group>
<contrib-group>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Abdellaoui]]></surname>
<given-names><![CDATA[Houssem]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
<contrib contrib-type="author">
<name>
<surname><![CDATA[Zrigui]]></surname>
<given-names><![CDATA[Mounir]]></given-names>
</name>
<xref ref-type="aff" rid="Aff"/>
</contrib>
</contrib-group>
<aff id="Af1">
<institution><![CDATA[,National Higher Engineering School of Tunis Research Laboratory LaTICE ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Tunisia</country>
</aff>
<aff id="Af2">
<institution><![CDATA[,University of Monastir Faculte des Sciences de Monastir ]]></institution>
<addr-line><![CDATA[ ]]></addr-line>
<country>Tunisia</country>
</aff>
<pub-date pub-type="pub">
<day>00</day>
<month>09</month>
<year>2018</year>
</pub-date>
<pub-date pub-type="epub">
<day>00</day>
<month>09</month>
<year>2018</year>
</pub-date>
<volume>22</volume>
<numero>3</numero>
<fpage>777</fpage>
<lpage>786</lpage>
<copyright-statement/>
<copyright-year/>
<self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_arttext&amp;pid=S1405-55462018000300777&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_abstract&amp;pid=S1405-55462018000300777&amp;lng=en&amp;nrm=iso"></self-uri><self-uri xlink:href="http://www.scielo.org.mx/scielo.php?script=sci_pdf&amp;pid=S1405-55462018000300777&amp;lng=en&amp;nrm=iso"></self-uri><abstract abstract-type="short" xml:lang="en"><p><![CDATA[Abstract: Our paper presents a distant supervision algorithm for automatically collecting and labeling &#8217;TEAD&#8216;, a dataset for Arabic Sentiment Analysis (SA), using emojis and sentiment lexicons. The data was gathered from Twitter during the period between the 1st of June and the 30th of November 2017. Although the idea of using emojis to collect and label training data for SA, is not novel, getting this approach to work for Arabic dialect was very challenging. We ended up with more than 6 million tweets labeled as Positive, Negative or Neutral. We present the algorithm used to deal with mixed-content tweets (Modern Standard Arabic MSA and Dialect Arabic DA). We also provide properties and statistics of the dataset alongside experiments results. Our tryouts covered a wide range of standard classifiers proved to be efficient for sentiment classification problem.]]></p></abstract>
<kwd-group>
<kwd lng="en"><![CDATA[Sentiment analysis]]></kwd>
<kwd lng="en"><![CDATA[opinion mining]]></kwd>
<kwd lng="en"><![CDATA[modern standard arabic]]></kwd>
<kwd lng="en"><![CDATA[arabic dialect]]></kwd>
<kwd lng="en"><![CDATA[sentiment dataset]]></kwd>
<kwd lng="en"><![CDATA[emojis]]></kwd>
<kwd lng="en"><![CDATA[sentiment lexicon]]></kwd>
</kwd-group>
</article-meta>
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