Language Use Matters: Analysis of the Linguistic Structure of Question Texts Can Characterize Answerability in Quora

Quora is one of the most popular community Q&A sites of recent times. However, many question posts on this Q&A site often do not get answered. In this paper, we quantify various linguistic activities that discriminates an answered question from an unanswered one. Our central finding is that the way users use language while writing the question text can be a very effective means to characterize answerability. This characterization helps us to predict early if a question remaining unanswered for a specific time period t will eventually be answered or not and achieve an accuracy of 76.26% (t = 1 month) and 68.33% (t = 3 months). Notably, features representing the language use patterns of the users are most discriminative and alone account for an accuracy of 74.18%. We also compare our method with some of the similar works (Dror et al., Yang et al.) achieving a maximum improvement of ~39% in terms of accuracy.Comment: 1 figure, 3 tables, ICWSM 2017 as poste

Learning to predict closed questions on stack overflow

The paper deals with the problem of predicting whether the user’s question will be closed by the moderator on Stack Overflow, a popular question answering service devoted to software programming. The task along with data and evaluation metrics was offered as an open machine learning competition on Kaggle platform. To solve this problem, we employed a wide range of classification features related to users, their interactions, and post content. Classification was carried out using several machine learning methods. According to the results of the experiment, the most important features are characteristics of the user and topical features of the question. The best results were obtained using Vowpal Wabbit – an implementation of online learning based on stochastic gradient descent. Our results are among the best ones in overall ranking, although they were obtained after the official competition was over

MOTIVATION TO RESPOND ON STACK OVERFLOW Q&A WEBSITE

Abstract. The importance of using Q&A sites such as Stack Overflow and Code Project, etc. is obvious toeveryone in order to solve the potential problems of the developers. The objective of this research was to increase the participation rate and responsiveness of developers on Stack Overflow website by improving the gamification methods. To present the proposed solution, a tool called Stack Overflow Super Gamification (SSG) was proposed, which is an extension for Eclipse. The purpose of this extension is to create an ongoing competition and motivation among developers to participate in answering questions on Stack Overflow site. In this extension, the ranking practices for active users on the siteare improved so that the continuity of participation in the site will earn more privileges. Also, the ranking structure of the users with various nationalities who have gained privileges was used to create a motivation and competition among the developers of different countries. Rewards for users in this extension, for example, offering superior job opportunities based on higher privileges, as well as providing an opportunity to advertise products or businesses and demonstrate personalabilities and talent for free, will make them more willing to participate, and will provide the incentive to stay active on the site. The proposed solutions will not only provide more activities and answers to more questions, but also bring valuable achievements to developers active on the site. According to the evaluations, the performance of the proposed solution for motivating developers to participate and answer the questions on the Stack Overflow site is acceptable. Since the purpose of this strategy is to encourage developers to participate effectively on the site, the evaluation results clearly reflect theusefulness of this solution in motivating developers. The results indicate that while the developers are actively involved, the number of unanswered questions, as well as unacceptable responses is reduced, and in the meanwhile, the quality of the responses given is acceptable in terms of brevity, completeness, and accuracy.Keywords: Gamification, Motivation on Stack Overflow website, Q&A sites

Asking Questions is Easy, Asking Great Questions is Hard: Constructing Effective Stack Overflow Questions

This paper explores and seeks to improve the ways in which Stack Overflow question posts can elicit answers. Using statistical data analysis approaches and reviews of existing literature, we pin- point three key factors that are found in many previously success- ful/answerable questions. We then present a prototypical sidebar for the ask page that leverages these factors to dynamically (1) evaluate the quality of questions in construction (2) display answer previews of relevant questions and (3) scaffold the identified factors to subsequent askers during their question development processes