
doi: 10.1109/mud.2014.14
Microblogging services are growing rapidly in the recent years. Twitter, one of the most popular microblogging sites, has gained more than 500 millions users. Thousands of developers are also using Twitter to communicate with one another and microblog about software-related topics such as programming languages, code libraries, etc. Understanding the behaviors of software microbloggers is one of the needed first steps toward building automated tools to encourage software microblogging activities and harness software microblogging to improve various software engineering activities. In this paper, we investigate the behaviors of software microbloggers in terms of their microblogging frequency, generated contents, and interactions among themselves. Our study is based on a dataset that contains more than 13 million microblogs generated by more than 42 thousands software microbloggers.
Databases and Information Systems, Social Media
Databases and Information Systems, Social Media
| selected citations These citations are derived from selected sources. This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | 14 | |
| popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network. | Average | |
| influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically). | Top 10% | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Top 10% |
