research-article

The future of online social networks (OSN)

Author:

Janice PenniAuthors Info & Claims

Telematics and Informatics, Volume 34, Issue 5

Pages 498 - 517

https://doi.org/10.1016/j.tele.2016.10.009

Published: 01 August 2017 Publication History

Abstract

Use of media content promotes the social usage patterns between the connected users.OSN cultivates the growing trend of video sharing more distinctly than photo content.Online videos alone domain the diffusion patterns of interactive activities on SNS.Key determinants impact the community structure for future use and adoption of OSN.Significant predictors foster the network structure of active users engaging on OSN. The explosion of online social networks (OSN) has created an interactive and communicative global phenomenon that has enabled billions of users to connect to other individuals on Facebook and Twitter but also with media sharing platforms such as Instagram and Pinterest. This study examines the current use of social media platforms and explores the factors that help define the long term implications of social media. The study employed a nationwide survey collected from 2012 to 2013 and is available from the PEW Internet research center of more than 2000 American citizens behaviour towards OSNs. The results revealed strong predictors of OSN that form the connections among users; and the core significant predictors: age, gender and access to mobile Internet that foster the adoption and usage of OSN in the future. Furthermore, online activities such as posting video content on social networks also highlighted the online usage patterns and trends of using social media to actively engage with other users more willingly than text. This is due to the viral nature of online media sharing on social media and as part of the video viewing and creating experience. An outline of practical implications of the findings and areas for future research is also discussed.

References

[1]

M.L. Abbott, J. McKinney, Wiley, US, 2013.

[2]

A. Afrasiabi Rad, M. Benyoucef, Measuring propagation in online social networks: the case of youtube, J. Inf. Syst. Appl. Res., 5 (2012) 26.

[3]

S. Aghaei, M.A. Nematbakhsh, H.K. Farsani, Evolution of the world wide web: from Web 1.0 to Web 4.0, Int. J. Web Semant. Technol., 3 (2012) 1-10.

[4]

A. Ahmad, A short description of social networking websites and its uses, Int. J. Adv. Comput. Sci. Appl., 2 (2011).

[5]

Akhgar, B., Fortune, D., Hayes, R.E., Guerra, B., Manso, M., 2013. Social media in crisis events: open networks and collaboration supporting disaster response and recovery. In: Paper Presented at the Technologies for Homeland Security (HST), 2013 IEEE International Conference on.

[6]

S. Alhabash, J.-H. Baek, C. Cunningham, A. Hagerstrom, To comment or not to comment?: How virality, arousal level, and commenting behavior on YouTube videos affect civic behavioral intentions, Comput. Hum. Behav., 51 (2015) 520-531.

Digital Library

[7]

Alhabash, S., McAlister, A.R., Rifon, N.J., Quilliam, E.T., Sternadori, M., Richards, J.I., 2013. A different take on virality: the relationship among motivations, uses, and viral behavioral intentions on Facebook and Twitter. In: Paper Presented at the American Academy of Advertising. Conference. Proceedings (Online).

[8]

R.P. Bagozzi, Y. Yi, Specification, evaluation, and interpretation of structural equation models, J. Acad. Mark. Sci., 40 (2012) 8-34.

[9]

Bakhshi, S., Shamma, D.A., Gilbert, E., 2014. Faces engage us: photos with faces attract more likes and comments on instagram. In: Paper Presented at the Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.

Digital Library

[10]

V. Barassi, E. Trer, Does Web 3.0 come after Web 2.0? Deconstructing theoretical assumptions through practice, New Media Soc., 14 (2012) 1269-1285.

[11]

F. Benevenuto, A. Pereira, T. Rodrigues, V. Almeida, J. Almeida, M. Gonalves, Characterization and analysis of user profiles in online video sharing systems, J. Inf. Data Manage., 1 (2010) 261.

[12]

F. Benevenuto, T. Rodrigues, V. Almeida, J. Almeida, K. Ross, Video interactions in online video social networks, ACM Trans. Multimedia Comput. Commun. Appl., 5 (2009) 1-25.

Digital Library

[13]

J.D. Brown, What is construct validity, JALT Test. Eval. SIG Newsl., 4 (2000) 7-10.

[14]

Burke, M., Kraut, R., Marlow, C., 2011. Social capital on Facebook: differentiating uses and users. In: Paper Presented at the Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.

Digital Library

[15]

J. Cha, Usage of video sharing websites: drivers and barriers, Telematics Inform., 31 (2014) 16-26.

Digital Library

[16]

H.K. Chan, X. Wang, E. Lacka, M. Zhang, A mixed-method approach to extracting the value of social media data, Prod. Oper. Manage. (2015).

[17]

M. Chan, Social identity gratifications of social network sites and their impact on collective action participation, Asian J. Soc. Psychol., 17 (2014) 229-235.

[18]

Chang, S., Kumar, V., Gilbert, E., Terveen, L.G., 2014. Specialization, homophily, and gender in a social curation site: findings from pinterest. In: Paper Presented at the Proceedings of the 17th ACM Conference on Computer Supported Cooperative Work & Social Computing.

Digital Library

[19]

S.-C. Chen, D.C. Yen, M.I. Hwang, Factors influencing the continuance intention to the usage of Web 2.0: an empirical study, Comput. Hum. Behav., 28 (2012) 933-941.

Digital Library

[20]

Cheng, A., Malit, M., Zhang, C., Koudas, N., 2014. SerpentTI: flexible analytics of users, boards and domains for pinterest. In: Paper Presented at the Proceedings of the 2014 ACM SIGMOD International Conference on Management of data.

Digital Library

[21]

X. Cheng, J. Liu, C. Dale, Understanding the characteristics of internet short video sharing: a YouTube-based measurement study, IEEE Trans. Multimedia, 15 (2013) 1184-1194.

Digital Library

[22]

C.M. Cheung, M.K. Lee, A theoretical model of intentional social action in online social networks, Decis. Support Syst., 49 (2010) 24-30.

Digital Library

[23]

C.M.K. Cheung, P.-Y. Chiu, M.K.O. Lee, Online social networks: why do students use facebook?, Comput. Hum. Behav., 27 (2011) 1337-1343.

Digital Library

[24]

K.C. Chinthakayala, C. Zhao, J. Kong, K. Zhang, A comparative study of three social networking websites, World Wide Web, 17 (2014) 1233-1259.

Digital Library

[25]

Choudrie, J., Vyas, A., Voros, T., Tsitsianis, N., 2013. Comparing the adopters and non-adopters of online social networks: a UK perspective. In: Paper Presented at the System Sciences (HICSS), 2013 46th Hawaii International Conference on.

Digital Library

[26]

W.S. Chow, S. Shi, Investigating customers satisfaction with brand pages in social networking sites, J. Comput. Inf. Syst., 55 (2015) 48-58.

[27]

E.K. Clemons, The complex problem of monetizing virtual electronic social networks, Decis. Support Syst., 48 (2009) 46-56.

Digital Library

[28]

T. Correa, A.W. Hinsley, H.G. de Ziga, Who interacts on the Web?: The intersection of users personality and social media use, Comput. Hum. Behav., 26 (2010) 247-253.

Digital Library

[29]

R. Crane, D. Sornette, Robust dynamic classes revealed by measuring the response function of a social system, Proc. Natl. Acad. Sci. U.S.A., 105 (2008) 15646.

[30]

J.J. Cronin, Get students pinterested in marketing and advertising, J. Advertising Educ., 17 (2013) 36.

[31]

R. Curras-Perez, C. Ruiz-Mafe, S. Sanz-Blas, Determinants of user behaviour and recommendation in social networks: an integrative approach from the uses and gratifications perspective, Ind. Manage. Data Syst., 114 (2014) 1477-1498.

[32]

Dawot, M., Intan, N., Ibrahim, R., 2014. A review of features and functional building blocks of social media. In: Paper Presented at the Software Engineering Conference (MySEC), 2014 8th Malaysian.

[33]

M. Duggan, Photo and Video Sharing Grow Online, Pew Research Internet Project, 2013.

[34]

M. Duggan, J. Brenner, Pew Research Centers Internet & American Life Project, Washington, DC, 2013.

[35]

M. Duggan, N.B. Ellison, C. Lampe, A. Lenhart, M. Madden, Social Media Update 2014, Pew Research Center, 2015.

[36]

A. Eftekhar, C. Fullwood, N. Morris, Capturing personality from Facebook photos and photo-related activities: how much exposure do you need?, Comput. Hum. Behav., 37 (2014) 162-170.

Digital Library

[37]

N.B. Ellison, Social network sites: definition, history, and scholarship, J. Comput. Mediated Commun., 13 (2007) 210-230.

Digital Library

[38]

N.B. Ellison, C. Steinfield, C. Lampe, The benefits of Facebook Friends: social capital and college students use of online social network sites, J. Comput. Mediated Commun., 12 (2007) 1143-1168.

[39]

Ferrara, E., Interdonato, R., Tagarelli, A., 2014. Online popularity and topical interests through the lens of instagram. In: Paper Presented at the Proceedings of the 25th ACM Conference on Hypertext and Social media.

Digital Library

[40]

C. Fornell, D.F. Larcker, Evaluating structural equation models with unobservable variables and measurement error, J. Mark. Res., 18 (1981) 39-50.

[41]

M. Fuduric, A. Mandelli, Communicating social media policies: evaluation of current practices, J. Commun. Manage., 18 (2014) 158-175.

[42]

L. Gao, X. Bai, An empirical study on continuance intention of mobile social networking services: integrating the IS success model, network externalities and flow theory, Qual. Res. Organiz. Manage., 26 (2014) 168-189.

[43]

F.J. Garrigos-Simon, R. Lapiedra Alcam, T. Barber Ribera, Social networks and Web 3.0: their impact on the management and marketing of organizations, Manage. Decis., 50 (2012) 1880-1890.

[44]

A.N. Geurin-Eagleman, L.M. Burch, Communicating via photographs: a gendered analysis of Olympic athletes visual self-presentation on Instagram, Sport Manage. Rev. (2014).

[45]

Gilbert, E., Bakhshi, S., Chang, S., Terveen, L., 2013. I need to try this?: a statistical overview of pinterest. In: Paper Presented at the Proceedings of the SIGCHI Conference on Human Factors in Computing Systems.

Digital Library

[46]

Grsun, G., Crovella, M., & Matta, I., 2011. Describing and forecasting video access patterns. In: Paper Presented at the INFOCOM, 2011 Proceedings IEEE.

[47]

N. Haferkamp, N.C. Krmer, Social comparison 2.0: examining the effects of online profiles on social-networking sites, Cyberpsychol Behav Soc. Netw., 14 (2011) 39-314.

[48]

J.F. Hair, Prentice Hall, Englewood Cliffs, N.J., London, 1998.

[49]

W. Hall, T. Tiropanis, Web evolution and web science, Comput. Netw., 56 (2012) 3859-3865.

Digital Library

[50]

J. Han, D. Choi, B.-G. Chun, T. Kwon, H.-C. Kim, Y. Choi, Collecting, organizing, and sharing pins in pinterest: interest-driven or social-driven?, ACM SIGMETRICS Perform. Eval. Rev., 42 (2014) 15-27.

Digital Library

[51]

X. Han, L. Wang, N. Crespi, S. Park, . Cuevas, Alike people, alike interests? Inferring interest similarity in online social networks, Decis. Support Syst., 69 (2015) 92-106.

Digital Library

[52]

R. Hanna, A. Rohm, V.L. Crittenden, Elsevier Advanced Technology Publications, Greenwich, 2011.

[53]

E. Hargittai, Y.-L.P. Hsieh, Predictors and consequences of differentiated practices on social network sites, Inf. Commun. Soc., 13 (2010) 515-536.

[54]

Haythornthwaite, C., 2002. Building social networks via computer networks: Creating and sustaining distributed learning communities. Building Virtual Communities: Learning and Change in Cyberspace, pp. 159-190.

[55]

J.H. Heinrichs, J.S. Lim, K.S. Lim, Influence of social networking site and user access method on social media evaluation, J. Consum. Behav., 10 (2011) 347-355.

[56]

D.L. Hoffman, T.P. Novak, Toward a deeper understanding of social media, J. Interact. Mark., 26 (2012) 69-70.

[57]

C.-L. Hsu, J.C.-C. Lin, Acceptance of blog usage: the roles of technology acceptance, social influence and knowledge sharing motivation, Inf. Manage., 45 (2008) 65-74.

Digital Library

[58]

C. Huang, T. Fu, H. Chen, Text-based video content classification for online video-sharing sites, J. Am. Soc. Inform. Sci. Technol., 61 (2010) 891-906.

Digital Library

[59]

C.J. Huberty, S. Olejnik, Applied MANOVA and discriminant analysis, vol. 2, Wiley-Interscience, Hoboken, N.J, 2006.

[60]

D.J. Hughes, M. Rowe, M. Batey, A. Lee, A tale of two sites: Twitter vs. Facebook and the personality predictors of social media usage, Comput. Hum. Behav., 28 (2012) 561-569.

Digital Library

[61]

L. Humphreys, Mobile social networks and social practice: a case study of Dodgeball, J. Comput. Mediated Commun., 13 (2007) 341-360.

Digital Library

[62]

L. Humphreys, Mobile social media: future challenges and opportunities, Mobile Media Commun., 1 (2013) 20-25.

[63]

R. Joiner, J. Gavin, M. Brosnan, J. Cromby, H. Gregory, J. Guiller, A. Moon, Gender, internet experience, internet identification, and internet anxiety: a ten-year followup, Cyberpsychol. Behav. Soc. Netw., 15 (2012) 37-372.

[64]

J.J. Jussila, H. Krkkinen, H. Aramo-Immonen, Social media utilization in business-to-business relationships of technology industry firms, Comput. Hum. Behav., 30 (2014) 606-613.

Digital Library

[65]

Y.S. Kang, J. Min, J. Kim, H. Lee, Roles of alternative and self-oriented perspectives in the context of the continued use of social network sites, Int. J. Inf. Manage., 33 (2013) 496.

[66]

A.M. Kaplan, M. Haenlein, Users of the world, unite! The challenges and opportunities of Social Media, Bus. Horiz., 53 (2010) 59-68.

[67]

Z. Katona, P.P. Zubcsek, M. Sarvary, Network effects and personal influences: the diffusion of an online social network, J. Mark. Res., 48 (2011) 425-443.

[68]

H. Khang, E.-J. Ki, L. Ye, Social media research in advertising, communication, marketing, and public relations, 19972010, J. Mass Commun. Q., 89 (2012) 279-298.

[69]

B. Kim, Understanding antecedents of continuance intention in social-networking services, Cyberpsychol. Behav. Soc. Netw., 14 (2011) 199-205.

[70]

B. Kim, J. Min, The distinct roles of dedication-based and constraint-based mechanisms in social networking sites, Internet Res., 25 (2015) 30-51.

[71]

C. Kim, M.-H. Jin, J. Kim, S. Namchu, User perception of the quality, value, and utility of user-generated content, J. Electron. Commerce Res., 13 (2012) 305-319.

[72]

J. Kim, P.S. Yu, N. Memon, Social network and high performance in smart communications, J. Supercomput., 66 (2013) 611-613.

Digital Library

[73]

Y. Kim, D. Sohn, S.M. Choi, Cultural difference in motivations for using social network sites: a comparative study of American and Korean college students, Comput. Hum. Behav., 27 (2011) 365-372.

Digital Library

[74]

Y.A. Kim, H.S. Song, Strategies for predicting local trust based on trust propagation in social networks, Knowl. Based Syst., 24 (2011) 1360-1371.

Digital Library

[75]

A. Klein, H. Ahlf, V. Sharma, Social activity and structural centrality in online social networks, Telematics Inform., 32 (2015) 321-332.

Digital Library

[76]

K. Kousha, M. Thelwall, M. Abdoli, The role of online videos in research communication: a content analysis of YouTube videos cited in academic publications, J. Am. Soc. Inform. Sci. Technol., 63 (2012) 1710-1727.

Digital Library

[77]

D. Kreps, K. Kimppa, Theorising Web 3.0: ICTs in a changing society, Inf. Technol. People, 28 (2015) 726-741.

[78]

Y.-C. Ku, R. Chen, H. Zhang, Why do users continue using social networking sites? An exploratory study of members in the United States and Taiwan, Inf. Manage., 50 (2013) 571-581.

Digital Library

[79]

O. Kwon, Y. Wen, An empirical study of the factors affecting social network service use, Comput. Hum. Behav., 26 (2010) 254-263.

Digital Library

[80]

S.J. Kwon, E. Park, K.J. Kim, What drives successful social networking services? A comparative analysis of user acceptance of Facebook and Twitter, Soc. Sci. J., 51 (2014) 534-544.

[81]

Lake, C., 2011. Online Video Sharing Doubles Within a Year.

[82]

R.S. Laurent, P. Turk, The effects of misconceptions on the properties of friedmans test, Commun. Stat. Simul. Comput., 42 (2013) 1596-1615.

[83]

Lenhart, A., Madden, M., 2007. Social Networking Websites and Teens: An Overview: Pew/Internet.

[84]

C.J. Lesko, Y.A. Hollingsworth, A new approach to communications management planning through 3D web and semantic web technologies, J. Manage. Strategy, 2 (2011) 25.

[85]

Li, H., 2014. Understanding Video Propagation in Online Social Networks: Measurement, Analysis, and Enhancement. Applied Sciences: School of Computing Science.

[86]

H. Li, X. Cheng, J. Liu, Understanding video sharing propagation in social networks: measurement and analysis, ACM Trans. Multimedia Comput.Commun. Appl., 10 (2014) 1-20.

Digital Library

[87]

Li, H., Liu, J., Xu, K., Wen, S., 2012. Understanding video propagation in online social networks. In: Paper Presented at the Proceedings of the 2012 IEEE 20th International Workshop on Quality of Service.

Digital Library

[88]

L.A. Liikkanen, A. Salovaara, Music on YouTube: User engagement with traditional, user-appropriated and derivative videos, Comput. Hum. Behav., 50 (2015) 108-124.

Digital Library

[89]

S. Lim, S.Y. Cha, C. Park, I. Lee, J. Kim, Getting closer and experiencing together: antecedents and consequences of psychological distance in social media-enhanced real-time streaming video, Comput. Hum. Behav., 28 (2012) 1365-1378.

Digital Library

[90]

K.-Y. Lin, H.-P. Lu, Why people use social networking sites: an empirical study integrating network externalities and motivation theory, Comput. Hum. Behav., 27 (2011) 1152-1161.

Digital Library

[91]

X. Lin, Y. Li, C.B. Califf, M. Featherman, Can social role theory explain gender differences in Facebook usage?, in: System Sciences (HICSS), 2013 46th Hawaii International Conference, IEEE, 2013, pp. 690-699.

Digital Library

[92]

S.-F. Lin, C.-L. Lin, D.-C. Lee, The relationship between elementary school teachers technology readiness and intention to use social media platforms for classroom management, Int. J. Organiz. Innov., 8 (2015) 48.

[93]

Linder, R., Snodgrass, C., Kerne, A., 2014. Everyday ideation: All of my ideas are on Pinterest. In: Paper Presented at the Proceedings of the 32nd annual ACM Conference on Human Factors in Computing Systems.

Digital Library

[94]

A. Loureiro, I. Messias, M. Barbas, Embracing Web 2.0 & 3.0 tools to support lifelong learning let learners connect, Proc. Soc. Behav. Sci., 46 (2012) 532-537.

[95]

Y. Lu, Y. Cao, B. Wang, S. Yang, A study on factors that affect users behavioral intention to transfer usage from the offline to the online channel, Comput. Hum. Behav., 27 (2011) 355-364.

Digital Library

[96]

X. Ma, H. Wang, H. Li, J. Liu, H. Jiang, Exploring sharing patterns for video recommendation on YouTube-like social media, Multimedia Syst., 20 (2014) 675-691.

Digital Library

[97]

M. Madden, A. Lenhart, M. Duggan, S. Cortesi, U. Gasser, Teens and Technology 2013, Pew Internet & American Life Project, 2013.

[98]

A. Malik, A. Dhir, M. Nieminen, Uses and Gratifications of digital photo sharing on Facebook, Telematics Inform., 33 (2015) 129-138.

Digital Library

[99]

L. Malita, Social media time management tools and tips, Proc. Comput. Sci., 3 (2011) 747-753.

[100]

Manikonda, L., Hu, Y., Kambhampati, S., 2014. Analyzing User Activities, Demographics, Social Network Structure and User-Generated Content on Instagram.

[101]

McNely, B.J., 2012. Shaping organizational image-power through images: Case histories of Instagram. In: Paper Presented at the Professional Communication Conference (IPCC), 2012 IEEE International.

[102]

Mendelson, A.L., Papacharissi, Z., 2010. Look at us: collective narcissism in college student Facebook photo galleries. The Networked Self: Identity, Community and Culture on Social Network Sites, pp. 251-273.

[103]

J.G. Miles, Instagram Power. Build Your Brand and Reach More Customers With the Power of Pictures, McGraw-Hill Education, The United States of America, 2014.

[104]

N.L. Muscanell, R.E. Guadagno, Make new friends or keep the old: Gender and personality differences in social networking use, Comput. Hum. Behav., 28 (2012) 107-112.

Digital Library

[105]

Nath, K., Dhar, S., Basishtha, S., 2014. Web 1.0 to Web 3.0-Evolution of the Web and its various challenges. In: Paper Presented at the Optimization, Reliability, and Information Technology (ICROIT), 2014 International Conference on.

[106]

J.C. Nunnally, Psychometric Theory, McGraw-Hill, New York, 1967.

[107]

Nyland, R., Near, C., 2007. Jesus is my friend: Religiosity as a mediating factor in Internet social networking use. In: Paper Presented at the AEJMC Midwinter Conference, Reno, NV.

[108]

Oinas-Kukkonen, H., Lyytinen, K., Yoo, Y., 2010. Social Networks and Information Systems: Ongoing and Future Research Streams.

[109]

Ong, C.-S., Day, M.-Y., 2010. An integrated evaluation model of user satisfaction with social media services. In: Paper Presented at the Information Reuse and Integration (IRI), 2010 IEEE International Conference on.

[110]

M. Pagani, C.F. Hofacker, R.E. Goldsmith, The influence of personality on active and passive use of social networking sites, Psychol. Mark., 28 (2011) 441-456.

[111]

P. Panzarasa, T. Opsahl, K.M. Carley, Patterns and dynamics of users behavior and interaction: network analysis of an online community, J. Am. Soc. Inform. Sci. Technol., 60 (2009) 911-932.

Digital Library

[112]

S.J. Park, Y.S. Lim, H.W. Park, Comparing Twitter and YouTube networks in information diffusion: the case of the Occupy Wall Street movement, Technol. Forecast. Soc. Change, 95 (2015) 208-217.

[113]

T.A. Pempek, Y.A. Yermolayeva, S.L. Calvert, College students social networking experiences on Facebook, J. Appl. Dev. Psychol., 30 (2009) 227-238.

[114]

Perrin, A., 2015. Social Media Usage: 20052015.

[115]

U. Pfeil, R. Arjan, P. Zaphiris, Age differences in online social networking a study of user profiles and the social capital divide among teenagers and older users in MySpace, Comput. Hum. Behav., 25 (2009) 643-654.

Digital Library

[116]

Pinto, H., Almeida, J. M., Gonalves, M.A., 2013. Using early view patterns to predict the popularity of youtube videos. In: Paper Presented at the Proceedings of the Sixth ACM International Conference on Web Search and Data Mining.

Digital Library

[117]

K. Purcell, Online Video 2013, Pew Research Center, 2013.

[118]

A. Quan-Haase, A.L. Young, Uses and gratifications of social media: a comparison of facebook and instant messaging, Bull. Sci. Technol. Soc., 30 (2010) 350-361.

[119]

J. Raacke, J. Bonds-Raacke, MySpace and facebook: applying the uses and gratifications theory to exploring friend-networking sites, Cyberpsychol. Behav., 11 (2008) 169-174.

[120]

L. Rainie, K. Purcell, A. Smith, The Social Side of the Internet, Pew Internet and American Life Project, 2011.

[121]

Rodrigues, T., Benevenuto, F., Almeida, V., Almeida, J., & Gonalves, M., 2009. A contextual analysis of the YouTube duplicate content. In: Paper Presented at the Proceedings of the XV Brazilian Symposium on Multimedia and the Web.

Digital Library

[122]

S.D. Roy, T. Mei, W. Zeng, S. Li, Towards cross-domain learning for social video popularity prediction, IEEE Trans. Multimedia, 15 (2013) 1255-1267.

Digital Library

[123]

M. Salehan, A. Negahban, Social networking on smartphones: when mobile phones become addictive, Comput. Hum. Behav., 29 (2013) 2632-2639.

Digital Library

[124]

H. Scheepers, R. Scheepers, R. Stockdale, N. Nurdin, The dependent variable in social media use, J. Comput. Inf. Syst., 54 (2014) 25-34.

[125]

P. Sedgwick, Multiple regression, BMJ, 347 (2013).

[126]

J.H. Sepanski, A modification on the friedman test statistic, Commun. Stat. Simul. Comput., 36 (2007) 783-790.

[127]

Siersdorfer, S., Chelaru, S., Nejdl, W., San Pedro, J., 2010. How useful are your comments?: analyzing and predicting youtube comments and comment ratings. In: Paper Presented at the Proceedings of the 19th International Conference on World Wide Web.

Digital Library

[128]

S. Siersdorfer, S. Chelaru, J.S. Pedro, I.S. Altingovde, W. Nejdl, Analyzing and mining comments and comment ratings on the social web, ACM Trans. Web, 8 (2014) 1-39.

Digital Library

[129]

Silva, T.H., de Melo, P.O., Almeida, J.M., Salles, J., Loureiro, A., 2013. A picture of Instagram is worth more than a thousand words: workload characterization and application. In: Paper Presented at the Distributed Computing in Sensor Systems (DCOSS), 2013 IEEE International Conference on.

Digital Library

[130]

D. Sledgianowski, S. Kulviwat, Using social network sites: the effects of playfulness, critical mass and trust in a hedonic context, J. Comput. Inf. Syst., 49 (2009) 74-83.

[131]

A.N. Smith, E. Fischer, C. Yongjian, How does brand-related user-generated content differ across YouTube, Facebook, and Twitter?, J. Interact. Mark., 26 (2012) 102-113.

[132]

A. Sophia van Zyl, The impact of Social Networking 2.0 on organisations, Electron. Library, 27 (2009) 906-918.

[133]

M. Spagnuolo, B. Falcidieno, 3D media and the semantic web, IEEE Intell. Syst., 24 (2009) 90-96.

Digital Library

[134]

W.P. Special, K.T. Li-Barber, Self-disclosure and student satisfaction with Facebook, Comput. Hum. Behav., 28 (2012) 624-630.

Digital Library

[135]

K. Subrahmanyam, S.M. Reich, N. Waechter, G. Espinoza, Online and offline social networks: use of social networking sites by emerging adults, J. Appl. Dev. Psychol., 29 (2008) 420-433.

[136]

E. Taufer, Wilcoxon-signed rank test for long memory sequences, Commun. Stat. Theory Methods, 38 (2009) 3240-3248.

[137]

M. Thelwall, D. Wilkinson, S. Uppal, Data mining emotion in social network communication: gender differences in MySpace, J. Am. Soc. Inform. Sci. Technol., 61 (2010) 190-199.

Digital Library

[138]

Trochim, W.M., 2006. Construct Validity.

[139]

Vartiainen, E., Vnnen-Vainio-Mattila, K., 2010. User experience of mobile photo sharing in the cloud. In: Paper Presented at the Proceedings of the 9th International Conference on Mobile and Ubiquitous Multimedia.

Digital Library

[140]

Viswanath, B., Mislove, A., Cha, M., Gummadi, K.P., 2009. On the evolution of user interaction in facebook. In: Paper Presented at the Proceedings of the 2nd ACM workshop on Online social networks.

Digital Library

[141]

Wang, D., Pedreschi, D., Song, C., Giannotti, F., Barabasi, A.-L., 2011. Human mobility, social ties, and link prediction. In: Paper Presented at the Proceedings of the 17th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining.

Digital Library

[142]

E.B. Weiser, The functions of Internet use and their social and psychological consequences, Cyberpsychol. Behav., 4 (2001) 723-743.

[143]

Wen, C., Tan, B. C., Chang, K.T.-T., 2009. Advertising effectiveness on social network sites: an investigation of tie strength, endorser expertise and product type on consumer purchase intention. In: ICIS 2009 Proceedings, 151.

[144]

W. Willinger, R. Rejaie, M. Torkjazi, M. Valafar, M. Maggioni, Research on online social networks: time to face the real challenges, ACM SIGMETRICS Perform. Eval. Rev., 37 (2010) 49-54.

Digital Library

[145]

W. Xie, Social network site use, mobile personal talk and social capital among teenagers, Comput. Hum. Behav., 41 (2014) 228-235.

Digital Library

[146]

C. Xu, S. Ryan, V. Prybutok, C. Wen, It is not for fun: an examination of social network site usage, Inf. Manage., 49 (2012) 210-217.

Digital Library

[147]

K. Xu, K. Zou, Y. Huang, X. Yu, X. Zhang, Mining community and inferring friendship in mobile social networks, Neurocomputing, 174 (2016) 605-616.

Digital Library

[148]

H. Yoganarasimhan, Impact of social network structure on content propagation: a study using YouTube data, Quant. Mark. Econ., 10 (2012) 111-150.

[149]

Zhang, L., Wang, F., Liu, J., 2014. Understand instant video clip sharing on mobile platforms: Twitters vine as a case study. In: Paper Presented at the Proceedings of Network and Operating System Support on Digital Audio and Video Workshop.

Digital Library

[150]

Zhou, J., Li, Y., Adhikari, V. K., Zhang, Z.-L., 2011. Counting youtube videos via random prefix sampling. In: Paper Presented at the Proceedings of the 2011 ACM SIGCOMM Conference on Internet Measurement Conference.

Digital Library

Cited By

Rouibah KAl-Qirim NAbbas HHwang Y(2022)Factors Affecting the Success of Social Commerce in Kuwaiti MicrobusinessesJournal of Global Information Management10.4018/JGIM.31394430:1(1-31)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.4018/JGIM.313944
Díaz Ferreyra NOstendorf SAïmeur EHeisel MBrand M(2022)ENAGRAM: An App to Evaluate Preventative Nudges for InstagramProceedings of the 2022 European Symposium on Usable Security10.1145/3549015.3555674(53-63)Online publication date: 29-Sep-2022
https://dl.acm.org/doi/10.1145/3549015.3555674
Roemmich KAndalibi N(2021)Data Subjects' Conceptualizations of and Attitudes Toward Automatic Emotion Recognition-Enabled Wellbeing Interventions on Social MediaProceedings of the ACM on Human-Computer Interaction10.1145/34760495:CSCW2(1-34)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1145/3476049
Show More Cited By

The future of online social networks (OSN)
1. Human-centered computing
  1. Human computer interaction (HCI)
    1. Interaction paradigms

Recommendations

Social exchange in online social networks. The reciprocity phenomenon on Facebook

Our research is focused on reciprocity, which is crucial for social exchanges.The online social network platform of our choice was Facebook, which is one of the most successful online social sites.In our study we found strong empirical evidence that an ...
Uses and gratifications of social networking sites for bridging and bonding social capital

Applying uses and gratifications theory (UGT) and social capital theory, our study examined users of four social networking sites (SNSs) (Facebook, Twitter, Instagram, and Snapchat), and their influence on online bridging and bonding social capital. ...
The 'WeTube' in YouTube – creating an online community through video sharing

Video sharing has become a growing social practice, with YouTube being the predominant online video sharing site. Most of the research concerning YouTube's social impact has been focused on quantitative evaluation of the social interaction facilitated ...

Comments

Please enable JavaScript to view thecomments powered by Disqus.

Information & Contributors

Information

Published In

cover image Telematics and Informatics

Telematics and Informatics Volume 34, Issue 5

August 2017

388 pages

ISSN:0736-5853

Issue’s Table of Contents

Copyright © Elsevier Ltd.

Publisher

Pergamon Press, Inc.

United States

Publication History

Published: 01 August 2017

Author Tags

Qualifiers

Research-article

Contributors

Other Metrics

View Article Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

5
Total Citations
View Citations
0
Total Downloads

Downloads (Last 12 months)0
Downloads (Last 6 weeks)0

Reflects downloads up to 14 Nov 2024

Other Metrics

View Author Metrics

Citations

Cited By

Rouibah KAl-Qirim NAbbas HHwang Y(2022)Factors Affecting the Success of Social Commerce in Kuwaiti MicrobusinessesJournal of Global Information Management10.4018/JGIM.31394430:1(1-31)Online publication date: 11-Nov-2022
https://dl.acm.org/doi/10.4018/JGIM.313944
Díaz Ferreyra NOstendorf SAïmeur EHeisel MBrand M(2022)ENAGRAM: An App to Evaluate Preventative Nudges for InstagramProceedings of the 2022 European Symposium on Usable Security10.1145/3549015.3555674(53-63)Online publication date: 29-Sep-2022
https://dl.acm.org/doi/10.1145/3549015.3555674
Roemmich KAndalibi N(2021)Data Subjects' Conceptualizations of and Attitudes Toward Automatic Emotion Recognition-Enabled Wellbeing Interventions on Social MediaProceedings of the ACM on Human-Computer Interaction10.1145/34760495:CSCW2(1-34)Online publication date: 18-Oct-2021
https://dl.acm.org/doi/10.1145/3476049
Aparicio-Martínez PRuiz-Rubio MPerea-Moreno AMartínez-Jiménez MPagliari CRedel-Macías MVaquero-Abellán M(2020)Gender differences in the addiction to social networks in the Southern Spanish university studentsTelematics and Informatics10.1016/j.tele.2019.10130446:COnline publication date: 1-Mar-2020
https://dl.acm.org/doi/10.1016/j.tele.2019.101304
Aparicio-Martnez PPerea-Moreno AMartinez-Jimenez MSuarez-Varela Varo IVaquero-Abelln M(2017)Social networks unnoticed influence on body image in Spanish university studentsTelematics and Informatics10.1016/j.tele.2017.08.00134:8(1685-1692)Online publication date: 1-Dec-2017
https://dl.acm.org/doi/10.1016/j.tele.2017.08.001

View Options

View options

Get Access

Login options

Check if you have access through your login credentials or your institution to get full access on this article.

Full Access

Get this Publication

Media

Figures

Other

Tables

View Issue’s Table of Contents