Yazar "Abbas, Ahmed K." seçeneğine göre listele

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    Öğe
    Estimation of Twitter user's nationality based on friends and followers information
    (Pergamon-Elsevier Science Ltd, 2018) Abbas, Ahmed K.; Bayat, Oğuz; Uçan, Osman Nuri
    Big Data has become very useful in many fields since it provides answers to many important questions that can significantly enhance decision making and process optimization. One of the most interesting domains in big data is the prediction of human features, facts and behaviors. In this paper a new and effective algorithm to predict the nationality of Twitter users is proposed. The proposed algorithm tries to prognosticate the Twitter user's location from their friend's location information only without needing GPS information. Although only approximately 30% of Twitter users write their location information in meaningful form, this paper proves that this percentage is enough to determine the nationality of any Twitter user correctly. The proposed algorithm is applied to estimate the thresholds that will be used to determine the nationality of Twitter users. The results show that our algorithm can correctly classify an average of 90% of the Twitter users. (C) 2017 Elsevier Ltd. All rights reserved.
  • [ X ]
    Öğe
    The prediction of fusion degree of International groups from their Twitter accounts
    (Ieee, 2017) Abbas, Ahmed K.; Mohammed, Tareq Abed; Bayat, Oğuz; Uçan, Osman Nuri; Bayat, Oğuz; Abbas, Ahmed K.; Mohammed, Tareq Abed
    Recently, social media has had a tremendous impact on our life and culture. Most of people enter the social media websites every day to do several things which makes them the most popular data sources on the Internet. According to this increasing impact of social media, many research works have done to study these websites, analyze them and predict useful information from them. Twitter is one of most popular and widely used social media network in the world. In this paper, a new efficient algorithm is proposed to solve society problem that does not discussed before which is the fusion degree of international groups on their new countries. During the many wars, political problems and other personal situations, many people changing their places and try to find better life in other countries. Therefore, it becomes very important for those new countries to simplify that task as can as possible and continuously follow the fusion process of those new coming persons in the society. The proposed algorithm in this paper will measure the fusion degree of international groups automatically from their twitter accounts. The proposed algorithm uses some features from the Twitter public information to estimate this degree. As a case study the new algorithm was applied on Arabic people in Turkey.