Taha Tobaili
http://data.open.ac.uk/person/3d6dc51619b334b8d501cf6974d5ac75
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Biography <p>I am a datascience PhD student conducting research in Sentiment Analysis for dialectal languages on social media with a specific focus for Arabic. Unlike other languages, Arabic is very dialectal and differs significantly among regions. Many Arabs tend to express their natural mother-tongue in text on social media without following a unified orthography. This unstructured form of language lacks semantic and linguistic resources, making it a challenge for the Arabic Natural Language Processing. Through my research I plan to leverage sentiment analysis methods to handle the heterogeneous Arabic social data. Extracting sentiment from text stems from my interest in Affective Computing: Developing machines that can understand, and react to, human emotion.</p>
Description <p>I am a datascience PhD student conducting research in Sentiment Analysis for dialectal languages on social media with a specific focus for Arabic. Unlike other languages, Arabic is very dialectal and differs significantly among regions. Many Arabs tend to express their natural mother-tongue in text on social media without following a unified orthography. This unstructured form of language lacks semantic and linguistic resources, making it a challenge for the Arabic Natural Language Processing. Through my research I plan to leverage sentiment analysis methods to handle the heterogeneous Arabic social data. Extracting sentiment from text stems from my interest in Affective Computing: Developing machines that can understand, and react to, human emotion.</p>
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Research overview I am a datascience PhD student conducting research in Sentiment Analysis for dialectal languages on social media with a specific focus for Arabic. Unlike other languages, Arabic is very dialectal and differs significantly among regions. Many Arabs tend to express their natural mother-tongue in text on social media without following a unified orthography. This unstructured form of language lacks semantic and linguistic resources, making it a challenge for the Arabic Natural Language Processing. Through my research I plan to leverage sentiment analysis methods to handle the heterogeneous Arabic social data. Extracting sentiment from text stems from my interest in Affective Computing: Developing machines that can understand, and react to, human emotion.
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Label Taha Tobaili
Depiction taha-tobaili.jpg
Family name Tobaili
Given name Taha
Mailbox SHA1 sum 5ad657ceb2c00d20c575814a749017630d84f30b
Name Taha Tobaili
Phone rn:tel:+44-(0)1908-54072

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