ارزیابی و پیش‌بینی عوامل کیفیت پاسخ‌ها در سیستم پرسش و پاسخ شبکه اجتماعی علمی ریسرچ گیت: مطالعه موردی قلمرو موضوعی مدیریت دانش

نویسندگان

دانشگاه شیراز، شیراز، ایران

چکیده

جوامع پرسش و پاسخ مجازی به افراد کمک می‌کنند که به اطلاعات مورد نیاز خود فراتر از پرس‌وجوهای مبتنی بر کلمات کلیدی سنتی و بازیابی اسناد و مدارک دست یابند. این جوامع به کاربران این امکان را می‌دهند که اطلاعات مورد نیاز خود را به‌صورت پرسش مطرح نمایند و پاسخ یا پاسخ‌هایی را از دیگر اعضا دریافت کنند. اما امکان تشخیص بهترین پاسخ از بین پاسخ‌ها و ارزیابی کیفیت آن‌ها به‌طور واضح و قطعی وجود ندارد. هدف این پژوهش ارزیابی و پیش‏بینی کیفیت پاسخ‌ها در شبکه اجتماعی-علمی «ریسرچ‌گیت» است. جهت دستیابی به این هدف، پرسش و پاسخ‏های واردشده به این شبکه در قلمرو موضوعی مدیریت دانش در بازه زمانی ماه ژانویه تا ماه می سال ۲۰۱۹ مورد بررسی قرار گرفت و اطلاعات مورد نیاز توسط خزنده سایت گردآوری شد. در نهایت، تعداد ۵۴ پرسش و ۴۴۳ پاسخ جهت تجزیه و تحلیل در دو سطح توصیفی و استنباطی توسط نرم‌افزار SPSS نسخه ۲۲ مورد بررسی قرار گرفت. نتایج نشان داد که به‌ترتیب متغیرهای مرتبط بودن، کفایت داشتن، و مختصر بودن با نسبت بخت‌های ۳/۶۲۶، ۳/۴۴ و ۳/۱۴۸ بیشترین قدرت پیش‌بینی درستی یا نادرستی پاسخ‌ها را دارند. در واقع، درستی پاسخ‌ها در صورت مرتبط بودن پاسخ دریافتی با پرسش به ‌میزان ۳/۶۲۶، درصورت وجود اطلاعات کافی در پاسخ به‌ میزان ۳/۴۴۰ و دریافت پاسخ‌های مختصر به‌ میزان ۳/۱۴۸ افزایش خواهد یافت.

کلیدواژه‌ها


عنوان مقاله [English]

Evaluating and Predicting the Quality of Answers Factors in the Research Gate’s Question and Answer System: a Case Study of the Thematic Domain of Knowledge Management

نویسندگان [English]

  • sahar Anbaraki
  • Abdolrasool Jowkar
چکیده [English]

Question answering (QA) helps one go beyond traditional keywords-based querying and retrieve information in more precise form than given by a document or a list of documents. These communities allow users to submit queries and receive answers or responses from other members. But, there is no clear way of evaluating the quality of that information. The purpose of this study was to evaluate and predict the quality of responses in the Research Gate Social Science Network. To achieve this goal, the questions and answers entered in the field from January to May 2019 surveyed in the field and the required information was collected by the site crawler. Finally, 54 questions and 443 answers were analyzed in descriptive and inferential levels by SPSS 22 software. The results show that the relevance, adequacy, and concordance variables with the odds ratios of 3.626, 3.440 and 3.148 have the most power to predict the correct or incorrect responses, respectively.

کلیدواژه‌ها [English]

  • Question and Answer System
  • Social Science Network
  • Research Gate
  • Quality Prediction of Responses
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