TY - JOUR
T1 - Inside the group
T2 - investigating social structures in player groups and their influence on activity
AU - Schiller, Michael Helfried
AU - Wallner, Günter
AU - Schinnerl, Christopher
AU - Monte Calvo, Alexander
AU - Pirker, Johanna
AU - Sifa, Rafet
AU - Drachen, Anders
PY - 2019/12/1
Y1 - 2019/12/1
N2 - Social features, matchmaking, and grouping functions are key elements of online multi-player experiences. Understanding how social connections form in and around games and their relationship to in-game activity offers insights for building and maintaining player bases and for improving engagement and retention. This paper presents an analysis of the groups formed by users of the the100.io - a social matchmaking website for different commercial titles, including Destiny on which we focus in this paper. Groups formed on the100.io can be described across a range of social network related metrics. Also, the social network formed within a group is evaluated in combination with user-provided demographic and preference data. Archetypal analysis is used to classify groups into archetypes and a correlation analysis is presented covering the effect of group characteristics on in-game-activity. Finally, weekly activity profiles are described. Our results indicate that group size as well as the number of moderators within a group and their connectedness to other team members influences a group's activity. We also identified four prototypical types of groups with different characteristics concerning composition, social cohesion, and activity.
AB - Social features, matchmaking, and grouping functions are key elements of online multi-player experiences. Understanding how social connections form in and around games and their relationship to in-game activity offers insights for building and maintaining player bases and for improving engagement and retention. This paper presents an analysis of the groups formed by users of the the100.io - a social matchmaking website for different commercial titles, including Destiny on which we focus in this paper. Groups formed on the100.io can be described across a range of social network related metrics. Also, the social network formed within a group is evaluated in combination with user-provided demographic and preference data. Archetypal analysis is used to classify groups into archetypes and a correlation analysis is presented covering the effect of group characteristics on in-game-activity. Finally, weekly activity profiles are described. Our results indicate that group size as well as the number of moderators within a group and their connectedness to other team members influences a group's activity. We also identified four prototypical types of groups with different characteristics concerning composition, social cohesion, and activity.
KW - Destiny
KW - Game analytics
KW - Matchmaking
KW - Social networks
UR - http://www.scopus.com/inward/record.url?scp=85089065237&partnerID=8YFLogxK
U2 - 10.1109/TG.2018.2858024
DO - 10.1109/TG.2018.2858024
M3 - Article
SN - 2475-1502
VL - 11
SP - 416
EP - 425
JO - IEEE Transactions on Games
JF - IEEE Transactions on Games
IS - 4
M1 - 8421042
ER -