YouTube has become one of the largest websites on the Internet. Among its many genres, both professional and amateur science communicators compete for audience attention. This article provides the first overview of science communication on YouTube and examines content factors that affect the popularity of science communication videos on the site. A content analysis of 390 videos from 39 YouTube channels was conducted. Although professionally generated content is superior in number, user-generated content was significantly more popular. Furthermore, videos that had consistent science communicators were more popular than those without a regular communicator. This study represents an important first step to understand content factors, which increases the channel and video popularity of science communication on YouTube.
AbishevaAGarimellaVRKGarciaDWeberI (2013) Who watches (and shares) what on YouTube? And when? Using Twitter to understand YouTube viewership. arXiv preprint arXiv:1312.4511. Available at: http://arxiv.org/pdf/1312.4511.pdf
2.
AcheKAWallaceLS (2008) Human papillomavirus vaccination coverage on YouTube. American Journal of Preventive Medicine35: 389–392.
AzerSA (2012) Can ‘YouTube’ help students in learning surface anatomy?Surgical and Radiologic Anatomy34: 465–468.
6.
BorgattiSPCrossR (2003) A relational view of information seeking and learning in social networks. Management Science49: 432–445.
7.
BorgholYArdonSCarlssonNEagerDMahantiA (2012) The untold story of the clones: Content-agnostic factors that impact YouTube video popularity. Paper presented at the 18th ACM SIGKDD conference, Beijing, China. Available at: http://www.ida.liu.se/~nikca/papers/kdd12.pdf
8.
BrossardD (2013) New media landscapes and the science information consumer. Proceedings of the National Academy of Sciences of the United States of America110: 14096–14101.
9.
BryantC (2003) Does Australia need a more effective policy of science communication?International Journal of Parasitology33: 357–361.
10.
BurgessJEGreenJB (2009) YouTube: Online Video and Participatory Culture. Cambridge: Polity Press.
11.
ChambersHE (2001) Effective Communication Skills for Scientific and Technical Professionals. New York, NY: Perseus Publishing.
12.
ChatzopoulouGShengCFaloutsosM (2010) A first step towards understanding popularity in YouTube. Paper presented at the IEEE INFOCOM 2010 conference, Riverside, CA. Available at: http://www.cs.unm.edu/~michalis/PAPERS/youtube_CAMERA.pdf
13.
ChauC (2010) YouTube as a participatory culture. New Directions for Youth Development2010: 65–74.
14.
ClaussenJECooneyPBDefilippiJMFoxSGGlaserSMHawkesE. (2013) Science Communication in a Digital Age: Social Media and the American Fisheries Society. Fisheries38: 359–362.
15.
CohenJ (1988) Statistical Power Analysis for the Behavioral Sciences. Mahwah, NJ: Lawrence Erlbaum Associates.
16.
Cran Team (2014) R: A Language and Environment for Statistical Computing (Version 3.0.2). Vienna: R Foundation for Statistical Computing. Available at: http://www.R-project.org/
17.
CraneRSornetteD (2008) Robust dynamic classes revealed by measuring the response function of a social system. Proceedings of the National Academy of Sciences of the United States of America105: 15649–15653.
18.
DavenportTHBeckJC (2001) The Attention Economy: Understanding the New Currency of Business. Boston, MA: Harvard Business Review Press.
EvansJD (1996) Straightforward Statistics for the Behavioral Sciences. Pacific Grove, CA: Brooks/Cole Publishing Company.
21.
FigueiredoFAlmeidaJMBenevenutoFGummadiKP (2014) Does content determine information popularity in social media? A case study of YouTube videos’ content and their popularity. Paper presented at the 32nd annual ACM conference, Toronto, ON, Canada. Available at: http://www.mpi-sws.org/~gummadi/papers/chi2014-contentpopularity.pdf
22.
FigueiredoFBenevenutoFAlmeidaJM (2011) The tube over time: Characterizing popularity growth of YouTube videos. Paper presented at the proceedings of the 4th ACM international conference, Hong Kong, China: Available at: http://homepages.dcc.ufmg.br/~fabricio/download/wsdm11.pdf
23.
GilbertJKStocklmayerSM (eds). (2013) Communication and Engagement with Science and Technology. New York, NY: Routledge.
HeathTMottaEPetreM (2007) Computing word-of-mouth trust relationships in social networks from semantic web and web 2.0 data sources. Paper presented at the 4th European semantic web conference, Innsbruck. Available at: http://oro.open.ac.uk/23610/1/ComputingWorld-of-Mouth.pdf
JenkinsHPurushotmaRWeigelMClintonKRobinsonAJ (2009) Confronting the challenges of participatory culture. Boston, MA: The John D. and Catherine T. MacArthur Foundation.
28.
JuhaszA (2009) Learning the five lessons of YouTube: After trying to teach there, I don’t believe the hype. Cinema Journal48: 145–150.
29.
KeelanJPavri-GarciaVTomlinsonGWilsonK (2007) YouTube as a source of information on immunization: A content analysis. JAMA: Journal of the American Medical Association298: 2482–2484.
30.
KimJ (2012) The institutionalization of YouTube: From user-generated content to professionally generated content. Media, Culture & Society34: 53–67.
LoASEsserMJGordonKE (2010) YouTube: A gauge of public perception and awareness surrounding epilepsy. Epilepsy & Behavior17: 541–545.
33.
LorencWArmstrongCAubrechtCGitlevichGHamptonQHeaneyM. (2013) 2013 YouTube Study. Columbia, MO: Columbia College.
34.
MillerNMaruyamaGBeaberRJValoneK (1976) Speed of speech and persuasion. Journal of Personality and Social Psychology34: 615–624.
35.
MinolKSpelsbergGSchulteEMorrisN (2007) Portals, blogs and co.: The role of the internet as a medium of science communication. Biotechnology Journal2: 1129–1140.
36.
MolyneauxHO’DonnellS (2008) Exploring the Gender Divide on YouTube: An Analysis of the Creation and Reception of Vlogs. American Communication Journal10: 8–22.
37.
MurugiahKVallakatiARajputKSoodAChallaNR (2011) YouTube as a source of information on cardiopulmonary resuscitation. Resuscitation82: 332–334.
38.
NisbetMCScheufeleDA (2009) What’s next for science communication? Promising directions and lingering distractions. American Journal of Botany96: 1767–1778.
39.
PandeyAPatniNSinghMSoodASinghG (2010) YouTube as a source of information on the H1N1 influenza pandemic. American Journal of Preventive Medicine38: 1–3.
SoodASarangiSPandeyAMurugiahK (2011) YouTube as a source of information on kidney stone disease. Urology77: 558–562.
46.
SudhaRD (2010) Advanced Communication Skills Laboratory Manual. New Delhi, India: Pearson Education.
47.
SzaboGHubermanBA (2010) Predicting the popularity of online content. Communications of the ACM53: 80–88.
48.
ValentiJM (1999) Commentary: How well do scientists communicate to media?Science Communication21: 172–178.
49.
WaskoJEricksonM (2009) The political economy of YouTube. In: SnickarsPVonderauP (eds) The YouTube Reader. Stockholm: National Library of Sweden, pp. 372–386.
50.
WeinsteinGGriffithsR (1992) Speech rate and listening comprehension: Further evidence of the relationship. TESOL Quarterly26: 385–390.
51.
YoganarasimhanH (2012) Impact of social network structure on content propagation: A study using YouTube data. QME: Quantitative Marketing and Economics10: 111–150.
ZhouRKhemmaratSGaoL (2010) The impact of YouTube recommendation system on video views. Paper presented at the 10th ACM SIGCOMM conference, New Delhi, India. Available at: http://conferences.sigcomm.org/imc/2010/papers/p404.pdf
