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    A machine learning approach to personal pronoun resolution in Turkish
    (2007) Yildirim S.; Kiliçaslan Y.
    In this paper, we present a machine learning based approach for estimating antecedents of anaphorically used personal pronouns in Turkish sentences using a decision tree classification technique coupled with the ensemble learning method. The technique learns from an annotated corpus, which has been compiled mostly from various popular child stories. Copyright © 2007, American Association for Artificial Intelligence (www.aaai.org). All rights reserved.
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    The relationship between levels of nomophobia prevalence and internet addiction among high school students: The factors influencing nomophobia
    (International Journal of Research in Education and Science, 2018) Gezgin D.M.; Cakir O.; Yildirim S.
    The purpose of this study is to investigate the relationship between nomophobia levels of high school students and their Internet Addiction. This study also investigates the factors including duration of smartphone and mobile Internet use that trigger and create this phenomenon. In order to explore the prevalence of nomophobia among high school students, the survey model was adopted in this study. As part of this survey, 929 high school students were randomly selected among 9th to 12th graders from Turkish high schools in different socioeconomic areas of Afyon, Ankara, and Mardin provinces. In the data collection process, a demographics questionnaire was employed, as well as a nomophobia scale and Internet addiction scale. According to the results, the nomophobia levels of high school students were found to be slightly above average. Pertaining to gender differences, female students have a higher tendency to exhibit nomophobic behaviors compared to male students. Additionally, students’ grade levels (which could also be considered as age) has no effect on the prevalence of nomophobia. Considering the duration of smartphone ownership, it was found that the longer the duration of smartphone usage, the higher the risk of exhibiting nomophobic behaviors. Finally, the results indicated that the higher the level of student Internet addiction, the more nomophobic behaviors they tend to exhibit. © 2018, International Journal of Research in Education and Science. All rights reserved.