
This paper investigated 12 years of full-text papers published in two conferences of computational linguistics. We investigated open code behaviors among researchers and gain insights into the effects of open code on citations. We found that the percentage of open-code papers increased by nearly one-third between 2006 and 2017. The papers with open code have more citations than papers without open code on average for most of the years and our regression models suggested that open code has a significant predictive effect on citations. Our results show that open code can be an effective way to receive visibility and attention for scholarly communication.
open code, citation analysis
open code, citation analysis
| 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). | 0 | |
| 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). | Average | |
| impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network. | Average |
