Name
Abstract | ||
|---|---|---|
The growing importance of citation-based bibliometric indicators in shaping the prospects of academic careers incentivizes scientists to boost the numbers of citations they receive. Whereas the exploitation of self-citations has been extensively documented, the impact of reciprocated citations has not yet been studied. We study reciprocity in a citation network of authors, and compare it with the average reciprocity computed in an ensemble of null network models. We show that obtaining citations through reciprocity correlates negatively with a successful career in the long term. Nevertheless, at the aggregate level we show evidence of a steady increase in reciprocity over the years, largely fuelled by the exchange of citations between coauthors. Our results characterize the structure of author networks in a time of increasing emphasis on citation-based indicators, and we discuss their implications towards a fairer assessment of academic impact. |
Year | Venue | Field |
|---|---|---|
2018 | arXiv: Physics and Society | Positive economics,Citation,Citation network,Reciprocity (social psychology),Artificial intelligence,Machine learning,Mathematics |
DocType | Volume | Citations |
Journal | abs/1808.03781 | 0 |
PageRank | References | Authors |
0.34 | 0 | 4 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Weihua Li | 1 | 5 | 5.17 |
| Tomaso Aste | 2 | 57 | 11.62 |
| Fabio Caccioli | 3 | 23 | 4.15 |
| Giacomo Livan | 4 | 9 | 3.78 |