Browsing Computer Science & Engineering by Publisher "Association for Computational Linguistics (ACL)"

Now showing items 1-11 of 11

    • A Characterization Study of Arabic Twitter Data with a Benchmarking for State-of-the-Art Opinion Mining Models 

      Baly, Ramy; Badaro, Gilbert; El-Khoury, Georges; Moukalled, Rawan; Aoun, Rita; ... more authors ( Association for Computational Linguistics (ACL) , 2017 , Conference Paper)
      Opinion mining in Arabic is a challenging task given the rich morphology of the language. The task becomes more challenging when it is applied to Twitter data, which contains additional sources of noise, such as the use ...

    • A light lexicon-based mobile application for sentiment mining of arabic tweets 

      Badaro, Gilbert; Baly, Ramy; Akel, Rana; Fayad, Linda; Khairallah, Jeffrey; ... more authors ( Association for Computational Linguistics (ACL) , 2015 , Conference Paper)
      Most advanced mobile applications require server-based and communication. This often causes additional energy consumption on the already energy-limited mobile devices. In this work, we provide to address these limitations ...

    • AraFacts: The First Large Arabic Dataset of Naturally-Occurring Professionally-Verified Claims 

      Ali, Zien Sheikh; Mansour, Watheq; Elsayed, Tamer; Al-Ali, Abdulaziz ( Association for Computational Linguistics (ACL) , 2021 , Conference Paper)
      We introduce AraFacts, the first large Arabic dataset of naturally-occurring claims collected from 5 Arabic fact-checking websites, e.g., Fatabyyano and Misbar, covering claims since 2016. Our dataset consists of 6,222 ...

    • ArCOV19-Rumors: Arabic COVID-19 Twitter Dataset for Misinformation Detection 

      Haouari, Fatima; Hasanain, Maram; Suwaileh, Reem; Elsayed, Tamer ( Association for Computational Linguistics (ACL) , 2021 , Conference Paper)
      In this paper we introduce ArCOV19-Rumors, an Arabic COVID-19 Twitter dataset for misinformation detection composed of tweets containing claims from 27th January till the end of April 2020. We collected 138 verified claims, ...

    • Are We Ready for this Disaster? Towards Location Mention Recognition from Crisis Tweets 

      Suwaileh, Reem; Imran, Muhammad; Elsayed, Tamer; Sajjad, Hassan ( Association for Computational Linguistics (ACL) , 2020 , Conference Paper)
      The widespread usage of Twitter during emergencies has provided a new opportunity and timely resource to crisis responders for various disaster management tasks. Geolocation information of pertinent tweets is crucial for ...

    • CAT: Credibility Analysis of Arabic Content on Twitter 

      El Ballouli, Rim; El-Hajj, Wassim; Ghandour, Ahmad; Elbassuoni, Shady; Hajj, Hazem; ... more authors ( Association for Computational Linguistics (ACL) , 2017 , Conference Paper)
      Data generated on Twitter has become a rich source for various data mining tasks. Those data analysis tasks that are dependent on the tweet semantics, such as sentiment analysis, emotion mining, and rumor detection among ...

    • Deep learning models for sentiment analysis in arabic 

      Al Sallab, Ahmad; Hajj, Hazem; Badaro, Gilbert; Baly, Ramy; El Hajj, Wassim; ... more authors ( Association for Computational Linguistics (ACL) , 2015 , Conference Paper)
      In this paper, deep learning framework is proposed for text sentiment classification in Arabic. Four different architectures are explored. Three are based on Deep Belief Networks and Deep Auto Encoders, where the input ...

    • Hulmona ( حلمنا ): The universal language model in arabic 

      ElJundi, Obeida; Antoun, Wissam; El Droubi, Nour; Hajj, Hazem; El-Hajj, Wassim; ... more authors ( Association for Computational Linguistics (ACL) , 2019 , Conference Paper)
      Arabic is a complex language with limited resources which makes it challenging to produce accurate text classification tasks such as sentiment analysis. The utilization of transfer learning (TL) has recently shown promising ...

    • IDRISI-RA: The First Arabic Location Mention Recognition Dataset of Disaster Tweets 

      Suwaileh, Reem; Imran, Muhammad; Elsayed, Tamer ( Association for Computational Linguistics (ACL) , 2023 , Conference Paper)
      Extracting geolocation information from social media data enables effective disaster management, as it helps response authorities; for example, in locating incidents for planning rescue activities, and affected people for ...

    • Methodical evaluation of Arabic word embeddings 

      Elrazzaz, Mohammed; Elbassuoni, Shady; Shaban, Khaled; Helwe, Chadi ( Association for Computational Linguistics (ACL) , 2017 , Conference Paper)
      Many unsupervised learning techniques have been proposed to obtain meaningful representations of words from text. In this study, we evaluate these various techniques when used to generate Arabic word embeddings. We first ...

    • QU-IR at SemEval 2016 Task 3: Learning to rank on Arabic community question answering forums with word embedding 

      Malhas, Rana; Torki, Marwan; Elsayed, Tamer ( Association for Computational Linguistics (ACL) , 2016 , Conference Paper)
      Resorting to community question answering (CQA) websites for finding answers has gained momentum in the past decade with the explosive rate at which social media has been proliferating. With many questions left unanswered ...