Online communities devoted to mobile games represent exemplary examples of competitive communities of practice, leveraging the competing forces of cooperation and competition to foster in-group solidarity and motivate members to further engage with the game and community. In this study, latent Dirichlet allocation was used to model conversation topics across over two million posts and comments made during a 3-year period on the r/grandorder subreddit, a competitive community of practice devoted to the mobile game Fate/Grand Order. In total, 20 distinct topics emerged spanning topical foci and emotional tones. The prevalence of certain topics, such as those related to gacha game mechanics, declined as community members mastered the practice and as the practice itself changed. Future studies should compare the structure and evolution of conversations across contexts, and they should likewise examine differences that emerge in discourse due to the relative balance of competitive and cooperative influences.
AmaghlobeliN. (2012). Linguistic features of typographic emoticons in SMS discourse. Theory and Practice in Language Studies, 2(2), 348–354. https://doi.org/10.4304/tpls.2.2.348-354
2.
ArunR.SureshV.MadhavanC. E. V.MurthyM. N. N. (2010). On finding the natural number of topics with latent Dirichlet allocation: Some observations. In ZakiM. J.YuJ. X.RavindranB.PudiV. (Eds.), Advances in knowledge discovery and data mining (pp. 391–402). Springer.
3.
BalakrishnanJ.GriffithsM. D. (2018). Loyalty towards online games, gaming addiction, and purchase intention towards online mobile in-game features. Computers in Human Behavior, 87, 238–246. https://doi.org/10.1016/j.chb.2018.06.002
BarrettM.CappelmanS.ShoibG.WalshamG. (2004). Learning in knowledge communities: Managing technology and context. European Management Journal, 22(1), 1–11. https://doi.org/10.1016/j.emj.2003.11.019
6.
BattyC.BerryM. (2016). Constellations and connections: The playful space of the creative practice research degree. Journal of Media Practice, 3, 181–194. https://doi.org/10.1080/14682753.2015.1116753
BleiD. M.NgA. Y.JordanM. I. (2003). Latent Dirichlet allocation. Journal of Machine Learning Research, 3, 993–1022. https://doi.org/10.5555/944919.944937
9.
BrittB. C. (under review). From cooperation to competition: A motivation-based contingency theory of communities of practice. Manuscript submitted to Journal of Knowledge Management.
10.
BrittB. C.BrittR. K.HayesJ. L.PanekE. T.MaddoxJ.MusaevA. (2020). Oral healthcare implications of dedicated online communities: A computational content analysis of the r/Dentistry subreddit. Health Communication. https://doi.org/10.1080/10410236.2020.1731937.
11.
BrittR. K.BrittB. C.HayesJ. L.OhJ. (2018). Mobile gacha games from Japan to the U.S.: The Tales of Link subreddit as a community of practice. Paper presented at the 2018 National Communication Association Conference, Salt Lake City, UT.
12.
BurrV. (2015). Social constructionism (3rd ed.). Routledge.
CuadraL.RíosS.L’HuillierG. (2011). Enhancing community discovery and characterization in VCoP using topic models. In 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology (pp. 326–329). IEEE.
17.
De ChoudhuryM.DeS. (2014). Mental health discourse on Reddit: Self-disclosure, social support, and anonymity. In Proceedings of the Eighth International AAAI Conference on Weblogs and Social Media (pp. 71–80). AAAI Press.
18.
DennenV. P. (2014). Becoming a blogger: Trajectories, norms, and activities in a community of practice. Computers in Human Behavior, 36, 350–358. https://doi.org/10.1016/j.chb.2014.03.028
19.
DeveaudR.SanJuanÉ.BellotP. (2014). Accurate and effective latent concept modeling for ad hoc information retrieval. Document numérique17(1), 61–84. https://doi.org/ 10.3166/DN.17.1.61-84
GriffithsT. L.SteyversM. (2004). Finding scientific topics. Proceedings of the National Academy of Sciences 101(suppl. 1), 5228–5235. https://doi.org/10.1073/pnas.0307752101
22.
GrünB.HornikK. (2011). topicmodels: An R package for fitting topic models. Journal of Statistical Software, 40(13), 1–30. https://doi.org/10.18637/jss.v040.i13
HsiaoK.-L.ChenC.-C. (2016). What drives in-app purchase intention for mobile games? An examination of perceived values and loyalty. Electronic Commerce Research and Applications, 16, 18–29. https://doi.org/10.1016/j.elerap.2016.01.001
25.
IkedaI.KobayashiT. (2009). Making democracy work via the functioning of heterogeneous personal networks: An empirical analysis based on a Japanese election study. In HsungR. M.LinN.BreigerR. (Eds.), Contexts of social capital: Social networks in markets, communities and families (p. 72–90). Routledge.
26.
JelodarH.WangY.YuanC.FengX.JiangX.LiY.ZhaoL. (2019). Latent Dirichlet allocation (LDA)and topic modeling: Models, applications, a survey. Multimedia Tools and Applications, 78, 15169–15211. https://doi.org/10.1007/s11042-018-6894-4
27.
JuanC.TianX.JintaoL.YongdongZ.ShengT. (2009). A density-based method for adaptive LDA model selection. Neurocomputing: 16th European Symposium on Artificial Neural Networks, 72(7–9), 1775–1781. https://doi.org/10.1016/j.neucom.2008.06.011
28.
KimppaK. K.HeimoO. I.HarviainenJ. T. (2015). First dose is always freemium. SIGCAS Computers & Society, 45(3), 132–137. https://doi.org/10.1145/2874239.2874258
29.
KobayashiT. (2010). Bridging social capital in online communities: Heterogeneity and social tolerance of online game players in Japan. Human Communication Research, 36, 546–569. https://doi.org/10.1111/j.1468-2958.2010.01388.x
LehtonenM. J.HarviainenJ. T. (2016). Mobile games and player communities: Designing for and with clans. Design Management Review, 27(3), 20–26. https://doi.org/10.1111/drev.12033
32.
MaierD.WaldherrA.MiltnerP.WiedemannG.NieklerA.KeinertA.PfetschB.HeyerG.ReberU.HausslerT.Schmid-PetriH.AdamS. (2018). Applying LDA topic modeling in communication research: Toward a valid and reliable methodology. Communication Methods and Measures, 12(2–3), 93–118. https://doi.org/10.1080/19312458.2018.1430754
33.
MohT.-S.BhagvatS. (2012). Clustering of technology tweets and the impact of stop words on clusters. In Proceedings of the 50th Annual Southeast Regional Conference. New York, NY: ACM. https://dl.acm.org/doi/pdf/10.1145/2184512.2184566
34.
MurilloE. (2008). Searching Usenet for virtual communities of practice: Using mixed methods to identify the constructs of Wenger’s theory. Information Research, 13(4). http://informationr.net/ir/13-4/paper386.html
PorteousI.NewmanD.IhlerA.AsuncionA.SmythP.WellingM. (2008). Fast collapsed Gibbs sampling for latent Dirichlet allocation. In Proceedings of the 14th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining (pp. 569–577). ACM.
RamosJ. (2003). Using tf-idf to determine word relevance in document queries. Paper presented at the First Instructional Conference on Machine Learning, Banff, Alberta, Canada.
ReerF.KrämerN. C. (2018). Are online role-playing games more social than multiplayer first-person shooters? Investigating how online gamers’ motivations and playing habits are related to social capital acquisition and social support. Entertainment Computing, 29, 1–9. https://doi.org/10.1016/j.entcom.2018.10.002
SagaR.KunimotoR. (2016). LDA-based path model construction process for structure equation modeling. Artificial Life and Robotics, 21(2), 155–159. https://doi.org/10.1007/s10015-016-0270-0
SnodgrassJ. G.BatchelderG.EisenhauerS.HowardL.DengahH. J. F.ThompsonR. S.BassarearJ.CooksonR. J.DefouwP. D.MattelianoM.PowellC. (2017). A guild culture of ‘casual raiding’ enhances its members’ online gaming experiences: A cognitive anthropological and ethnographic approach toWorld of Warcraft. New Media & Society, 19(12), 1927–1944. https://doi.org/10.1177/1461444816644804
StavaracheL. L.DascaluM.Trausan-MatuS.NistorN. (2015). How does time shape a virtual community of practice? In The 11th International Scientific Conference eLearning and software for Education (pp. 380–386). National Defence University.
56.
ThompsonM. J. (2017). Collective intentionality, social domination, and reification. Journal of Social Ontology, 3(2), 207–229. https://doi.org/10.1515/jso-2016-0017
WaskoM. M.FarajS. (2000). “It is what one does”: Why people participate and help others in electronic communities of practice. Journal of Strategic Information Systems, 9, 155–173. https://doi.org/10.1016/S0963-8687(00)00045-7
WengerE. (1998). Communities of practice: Learning, meaning, and identity. Cambridge University Press.
65.
WengerE.McDermottR.SnyderW. (2002). Cultivating communities of practice: A guide to managing knowledge. Harvard Business School Press.
66.
WolfeJ.HaghighiA. D.KleinD. (2008). Fully distributed EM for very large datasets. In Proceedings of the International Conference on Machine Learning (pp. 1184–1191). ACM.
67.
ZendleD.MeyerR.OverH. (2019). Adolescents and loot boxes: Links with problem gambling and motivations for purchase. Royal Society Open Science, 6, 190049. https://doi.org/10.1098/rsos.190049
68.
ZinaidaS. (2016). Narratives in science: Language and culture challenges of today. European Journal of Humanities and Social Sciences, 1, 7–10. https://doi.org/10.29013/EJHSS-16-1-7-10
