WoS İndeksli Yayınlar Koleksiyonu

Permanent URI for this collectionhttps://hdl.handle.net/20.500.12416/8653

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Access Right: Closed AccessAuthor: search.filters.author.Uysal, Elif

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  • Conference Object
    Spend Portal: Linked Data Discovery Using Sparql Endpoints
    (Ieee, 2017) Yumusak, Semih; Aras, Riza Emre; Uysal, Elif; Dogdu, Erdogan; Kodaz, Halife; Oztoprak, Kasim
    We present the project SpEnD, a complete SPARQL endpoint discovery and analysis portal. In a previous study, the SPARQL endpoint discovery and analysis steps of the SpEnD system were explained in detail. In the SpEnD portal, the SPARQL endpoints are extracted from the web by using web crawling techniques, monitored and analyzed by live querying the endpoints systematically. After many sustainability improvements in the SpEnD project, the SpEnD system is now online as a portal. SpEnD portal currently serves 1487 SPARQL endpoints, out of which 911 endpoints are uniquely found by SpEnD only when compared to the other existing SPARQL endpoint repositories. In this portal, the analytic results and the content information are shared for every SPARQL endpoint. The endpoints stored in the repository are monitored and updated continuously.
  • Conference Object
    Citation - WoS: 8
    Citation - Scopus: 11
    Sentiment Analysis for the Social Media: a Case Study for Turkish General Elections
    (Assoc Computing Machinery, 2017) Yumusak, Semih; Oztoprak, Kasim; Dogdu, Erdogan; Uysal, Elif
    The ideas expressed in social media are not always compliant with natural language rules, and the mood and emotion indicators are mostly highlighted by emoticons and emotion specific keywords. There are language independent emotion keywords (e.g. love, hate, good, bad), besides every language has its own particular emotion specific keywords. These keywords can be used for polarity analysis for a particular sentence. In this study, we first created a Turkish dictionary containing emotion specific keywords. Then, we used this dictionary to detect the polarity of tweets that are collected by querying political keywords right before the Turkish general election in 2015. The tweets were collected based on their relatedness with three main categories: the political leaders, ideologies, and political parties. The polarity of these tweets are analyzed in comparison with the election results.