Using Sessions from Clickstream Data Analysis to Uncover Different Types of Twitter Behaviour
| dc.contributor.author | Meier, Florian | |
| dc.contributor.author | Aigner, Johannes | |
| dc.contributor.author | Elsweiler, David | |
| dc.date.accessioned | 2025-06-18T16:34:32Z | |
| dc.date.available | 2025-06-18T16:34:32Z | |
| dc.date.issued | 2017-01-01 | |
| dc.description.abstract | While much is known about how Twitter is used for specific tasks or by particular groups of users, we understand surprisingly little about how the service is used generally on a daily basis. To learn more about general Twitter behaviour we perform a cluster analysis on a rich set of longitudinal interaction log data describing interactions 44 users had with the Twitter website over a 5 month period. We report on and interpret 5 clusters representing common usage patterns with the service. | |
| dc.description.epage | 250 | |
| dc.description.spage | 237 | |
| dc.identifier.doi | 10.18452/1452 | |
| dc.identifier.issn | 1633-1311 | |
| dc.identifier.openaire | doi_dedup___:cb9b8d745ffcfe503f3a8ee76447299e | |
| dc.identifier.uri | https://ror.circle-u.eu/handle/123456789/1138583 | |
| dc.openaire.affiliation | Humboldt-Universität zu Berlin | |
| dc.openaire.collaboration | 1 | |
| dc.publisher | Humboldt-Universität zu Berlin | |
| dc.rights | OPEN | |
| dc.source | Ingénierie Des Systèmes D'information | |
| dc.subject | 020 Bibliotheks- und Informationswissenschaften | |
| dc.subject | information behaviour | |
| dc.subject | ||
| dc.subject | ddc:020 | |
| dc.subject | 020 Bibliotheks- und Informationswissenschaft | |
| dc.subject | clickstream data | |
| dc.subject | clustering | |
| dc.subject.fos | 0202 electrical engineering, electronic engineering, information engineering | |
| dc.subject.fos | 02 engineering and technology | |
| dc.title | Using Sessions from Clickstream Data Analysis to Uncover Different Types of Twitter Behaviour | |
| dc.type | publication |