
Hand-made hyperlinks are increasingly outnumbered by automatically generated links, which are usually based on text similarity or some sort of recommendation algorithm. In this paper we explore the current linking and appreciation of automatically generated links. To what extent do they prevail on the Web, in what forms do they appear, and do users think those generated links are just as good as human-created links? To answer these questions we first propose a model for extracting contextual information of a hyperlink. Second, we developed a hyperlink ranker to assigned relevance to each existing human generated link. With the outcomes of the hyperlink ranker, together with another two recommendation strategies, we performed a user study with over 100 participants. Results indicate that automated links are "good enough", and even preferred in some user contexts. Still, they do not provide the deeper knowledge as expressed by human authors.
| 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). | 1 | |
| 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 |
