Proximity dimensions and the emergence of collaboration: a HypTrails study on German AI research
Zitieren Sie bitte immer diese URN: urn:nbn:de:bvb:20-opus-269831
- Creation and exchange of knowledge depends on collaboration. Recent work has suggested that the emergence of collaboration frequently relies on geographic proximity. However, being co-located tends to be associated with other dimensions of proximity, such as social ties or a shared organizational environment. To account for such factors, multiple dimensions of proximity have been proposed, including cognitive, institutional, organizational, social and geographical proximity. Since they strongly interrelate, disentangling these dimensions andCreation and exchange of knowledge depends on collaboration. Recent work has suggested that the emergence of collaboration frequently relies on geographic proximity. However, being co-located tends to be associated with other dimensions of proximity, such as social ties or a shared organizational environment. To account for such factors, multiple dimensions of proximity have been proposed, including cognitive, institutional, organizational, social and geographical proximity. Since they strongly interrelate, disentangling these dimensions and their respective impact on collaboration is challenging. To address this issue, we propose various methods for measuring different dimensions of proximity. We then present an approach to compare and rank them with respect to the extent to which they indicate co-publications and co-inventions. We adapt the HypTrails approach, which was originally developed to explain human navigation, to co-author and co-inventor graphs. We evaluate this approach on a subset of the German research community, specifically academic authors and inventors active in research on artificial intelligence (AI). We find that social proximity and cognitive proximity are more important for the emergence of collaboration than geographic proximity.…
Autor(en): | Tobias Koopmann, Maximilian Stubbemann, Matthias Kapa, Michael Paris, Guido Buenstorf, Tom Hanika, Andreas Hotho, Robert Jäschke, Gerd Stumme |
---|---|
URN: | urn:nbn:de:bvb:20-opus-269831 |
Dokumentart: | Artikel / Aufsatz in einer Zeitschrift |
Institute der Universität: | Fakultät für Mathematik und Informatik / Institut für Informatik |
Sprache der Veröffentlichung: | Englisch |
Titel des übergeordneten Werkes / der Zeitschrift (Englisch): | Scientometrics |
ISSN: | 1588-2861 |
Erscheinungsjahr: | 2021 |
Band / Jahrgang: | 126 |
Heft / Ausgabe: | 12 |
Seitenangabe: | 9847–9868 |
Originalveröffentlichung / Quelle: | Scientometrics 2021, 126(12):9847–9868. DOI: 10.1007/s11192-021-03922-1 |
DOI: | https://doi.org/10.1007/s11192-021-03922-1 |
Allgemeine fachliche Zuordnung (DDC-Klassifikation): | 0 Informatik, Informationswissenschaft, allgemeine Werke / 00 Informatik, Wissen, Systeme / 004 Datenverarbeitung; Informatik |
Freie Schlagwort(e): | co-authorships; co-inventorships; collaboration; dimensions of proximity; embedding techniques |
Datum der Freischaltung: | 14.06.2022 |
Lizenz (Deutsch): | CC BY: Creative-Commons-Lizenz: Namensnennung 4.0 International |