Title
Influence of controlled and uncontrolled interventions on Twitter in different target groups
Author
van Maanen, P.P.
Aarts, O.
Boertjes, E.
Wijn, R.
Publication year
2013
Abstract
In this paper the influence of interventions on Twitter users is studied. We define influence in a) number of participants, b) size of the audience, c) amount of activity, and d) reach. Influence is studied for four different target groups: a) politicians, b) journalists, c) employees and d) the general public. Furthermore, two types of interventions are studied: a) by all Twitter users (i.e., uncontrolled interventions), and b) those tweeted by an organization that benefits from any resulting influence (i.e., controlled interventions). As a case study, tweets about a large Dutch governmental organization are used. Results show a clear relation between the number of uncontrolled interventions and influence in all four target groups, for each of the defined types of influence. Controlled interventions show less influence: Significant influence was found for the general public, but influence for politicians and employees was only mildly significant, and no influence was found for journalists. The effect found for uncontrolled interventions however suggests that this influence is indeed reachable for some target groups, even when the number of interventions is small, and very well reachable for all target groups, provided the number of interventions is large enough. In addition to this we found that interventions influence groups to a different extent. Own employees were influenced strongest, differing significantly from the other groups.
Subject
Human GI Innovation in Behaviour / Gedrag en Innovatie
PCS - Perceptual and Cognitive Systems
BSS - Behavioural and Societal Sciences ETP - Enabling Technology Programs
Psychology
Information Society
Social Media
Twitter
Behavioural influence
ETP SON-M
Social influence
To reference this document use:
http://resolver.tudelft.nl/uuid:8507431a-2d27-42ce-b406-b29d87d38cd6
DOI
https://doi.org/10.1145/2492517.2492563
TNO identifier
486559
Source
ASONAM '13 Proceedings of the 2013 IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining, 712-719
Document type
conference paper