Folksonomy Based Trend Analysis on Community Question Answering Sites: A Perspective on Software Technologies

In the booming era of online social media environment, community question answering (CQA) sites have become one of the popular resources for software engineers and software industries. Software engineers are increasingly sharing their questions and answers on CQA sites. Aims of the CQA sites are to provide useful and relevant information to the users. Analysis information of major programming languages using trend analysis can be useful for software engineers to understand the technological evolutions and popularity. Since most of the CQA sites consist of user assigned tags by which folksonomy can be efficiently utilized for developing suitable algorithm to find the trend of key programming technologies. In this paper, two techniques of trend analysis, namely, ARIMA time series model and fuzzy time series model have been applied on the tagging data to identify the trend. Trend analysis is being carried on key programming languages, namely, c#, Java, PHP, and python. In this paper, quality of the trend is measured by entropy, Z
_Trend
, and quality of forecast is measured by MMRE, burst trend for key programming languages.