CoChat
Sign Up
Cited by 266Impact of Technology on AdolescentsMedia and Digital CommunicationTechnology Adoption and User Behaviour

The DOI matches its Crossref record; 95 of the 96 references it cites were found in a registry or an index, and 1 are not checked yet; none of the 21 sources its claims cite is checked for support yet.

Social media addiction: What is the role of content in YouTube?

Open access
Balakrishnan, Janarthanan, Griffiths, Mark D.·2017·Journal of Behavioral Addictions
DOI 10.1556/2006.6.2017.058PMC PMC5700732
Open this paper in CoChat — free accountOpen PDF

Abstract

Background: YouTube, the online video creation and sharing site, supports both video content viewing and content creation activities. For a minority of people, the time spent engaging with YouTube can be excessive and potentially problematic. Method: This study analyzed the relationship between content viewing, content creation, and YouTube addiction in a survey of 410 Indian-student YouTube users. It also examined the influence of content, social, technology, and process gratifications on user inclination toward YouTube content viewing and content creation. Results: The results demonstrated that content creation in YouTube had a closer relationship with YouTube addiction than content viewing. Furthermore, social gratification was found to have a significant influence on both types of YouTube activities, whereas technology gratification did not significantly influence them. Among all perceived gratifications, content gratification had the highest relationship coefficient value with YouTube content creation inclination. The model fit and variance extracted by the endogenous constructs were good, which further validated the results of the analysis. Conclusion: The study facilitates new ways to explore user gratification in using YouTube and how the channel responds to it.

Checked 2026-10-09 · 1 reference not checked yet

Overview

AI snapshot

Written from the paper’s full text.

TL;DR

This survey of 410 Indian student YouTube users examined how content viewing and content creation relate to YouTube addiction, and how four perceived gratifications (content, social, process, technology) influence those activities. Content creation had a stronger relationship with YouTube addiction than content viewing, and social gratification significantly influenced both viewing and creation.

Key findings

  • YouTube content creation inclination had a stronger positive relationship with YouTube addiction (β = 0.512, p < .001) than content viewing inclination (β = 0.319, p < .001).
  • Content gratification had the highest relationship with YouTube content creation inclination (β = 0.660, p < .001), while it was not significantly related to content viewing inclination.
  • Social gratification significantly influenced both content creation (β = 0.294, p < .001) and content viewing (β = 0.277, p < .001); process gratification significantly influenced content viewing (β = 0.442, p < .001) but not content creation.
  • Technology gratification was not significantly related to either content creation or content viewing, and mediation analysis found content, social, and process gratifications had significant indirect effects on YouTube addiction via viewing/creation, whereas technology gratification did not.

Methods

  • A survey of 410 Indian student YouTube users: 243 men (59.3%) and 167 women (40.7%); 219 undergraduates, 165 postgraduates, and 26 doctoral students. Respondents averaged 44.66 min/day on YouTube during working hours and 70.55 min/day during non-working hours.
  • The questionnaire included 38 statements measuring content, social, process, and technology gratifications; YouTube content viewing and creation affinity; and YouTube addiction. The YouTube Addiction Scale (six items) was adapted from the Bergen Facebook Addiction Scale by replacing “Facebook” with “YouTube.”
  • Hierarchical structural equation modeling was used, with first- and second-order measurement models, maximum likelihood estimation, Baron and Kenny mediation analysis, and 2,000 bootstrap iterations; MANOVA and ANOVA examined gender and age differences.

Limitations

  • The paper states the study was confined to content viewing and content creation as major YouTube addiction variables, used a non-clinical convenience Indian-student sample aged 16–34, and relied on self-report and self-selected data subject to recall and social desirability biases.
  • The paper notes future research should use clinical and non-clinical samples from other countries and age ranges, examine mature age groups, explore more gratifications, and study content creation and viewing separately.
  • Evident from the design: the cross-sectional survey cannot establish causal direction between gratifications, YouTube activities, and addiction, and the addiction measure was adapted from a Facebook scale rather than developed specifically for YouTube.

Model-written summary. Check it against the paper before relying on it.

Integrity signals

Registry

Crossref · 10.1556/2006.6.2017.058

Cites

95 of 96 references verified0 citation errors · 0 not checkable

Statistics

Nothing to recompute.

Verification

Claims the paper makes

0 of 21 cited sources checked · 0 supported · 0 flagged

Show all 33 claims

  • It may state two separate claims as one. 28
  • Probably not a substantial claim. 20
  • The quote only partly states this claim. 2
40 of 40

  • The paper relies on this without support.

    YouTube allows two major user functions: content creation and content seeking.

    “YouTube allows two major user functions (i.e., content creation and content seeking).”

  • The paper relies on this without support.

    There have been few studies that have analyzed user gratification and addiction to YouTube use.

    “There have been few studies that have analyzed user gratification and addiction to YouTube use.”

  • The paper relies on this without support.

    The multiple functions offered by YouTube have attracted many users to it.

    “The multiple functions offered by YouTube have attracted many users to it.”

  • The paper relies on this without support.

    The uniqueness of YouTube as an entertainment medium is that it facilitates both content viewing and creation activities.

    “The uniqueness of YouTube as an entertainment medium is that it facilitates both content viewing and creation activities.”

  • The paper relies on this without support.

    Content creation is a dynamic activity that incorporates both personal satisfaction and social approval.

    “Content creation is a dynamic activity that incorporates both personal satisfaction and social approval.”

  • The paper relies on this without support.

    Content creation is an enhanced function of user engagement.

    “Content creation is an enhanced function of user engagement.”

  • The paper relies on this without support.

    Content creation is a passionate activity, unlike content viewing, which is largely passive.

    “Content creation is a passionate activity, unlike content viewing, which is largely passive.”

  • The paper relies on this without support.

    Communication and content are the basics for building a social interpersonal relationship.

    “Communication and content are the basics for building a social interpersonal relationship.”

  • The paper relies on this without support.

    Self-documentation is dependent upon content.

    “Similarly, self-documentation is dependent upon content.”

  • The paper relies on this without support.

    Although there is no monetary reward associated with content creation, users create video content on YouTube to create and share videos exhibiting their interest and passion and comment on those that pique their interest.

    “Although there is no monetary reward associated with content creation, users create video content on YouTube to create and share videos exhibiting their interest and passion and comment on those that pique their interest.”

  • The paper relies on this without support.

    Technology is an important factor that encourages users to engage in any social media domain.

    “Technology is an important factor that encourages users to engage in any social media domain.”

  • The paper relies on this without support.

    Students are the relevant sample for the study objectives.

    “Although students are considered to be the relevant sample for the study objectives”
12 of 12

Claims other papers make about this one

Each is checked against this paper’s own text: does it say what the citing paper says it does?

Self-check

Percentages, sums and reported differences re-computed from the paper’s own numbers.

Each contradiction between two passages listed here was confirmed by an independent check.

  • Content-gratification coefficient disagrees with Table 5

    Major

    The text gives the content-gratification-to-creation coefficient as 0.569, whereas Table 5 gives 0.660 for that relationship.

  • Social-gratification coefficients disagree with Table 5

    Major

    The text reports coefficients of 0.256 for content creation and 0.281 for content viewing. Table 5 reports 0.294 and 0.277, respectively.

  • Content-viewing variance is reported as both .300 and .207

    Major

    The structural-model text reports r2 = .300 for YouTube content viewing inclination, but Table 5 reports .207 for the same outcome.

  • Self-expression √AVE disagrees with its reported AVE

    Minor

    Table 2 reports self-expression AVE as .623, whose square root is about .789. Table 3 instead lists its √AVE as .831.

  • Process gratification's indirect effect is smaller than its direct effect

    Minor

    The discussion says indirect effects are higher than direct effects for content, process, and social gratifications. For process gratification, Table 6 gives an indirect effect of 0.366 and a direct effect of −0.487, which is larger in magnitude.

  • Addiction variance is reported as 30% despite r2 = .404

    Minor

    The sentence assigns YouTube addiction an r2 of .404 but says its predictors account for 30% of the variance. An r2 of .404 represents 40.4%, not 30%.

  • Social-gratification viewing coefficient also differs from Table 5

    Minor

    The reported viewing coefficient of 0.281 differs from the 0.277 shown for the same relationship in Table 5.

7 of 7

Citations

Cites

Flagged first, then by citations

Show all 96 references

Research works printed but not linked: 100

  1. Edwards, 1993, Development of a new scale for measuring compulsive buying behavior, Financial Counseling and Planning,, 4, 67
  2. Lange, 2007, a Commenting on comments : Investigating responses to antagonism on YouTube Proceedings of the Society for Conference, Applied Anthropology
  3. Weiyan, 2015, A historical overview of uses and gratifications theory, Cross-Cultural Communication,, 11, 71
  4. Hong, 2014, Analysis of the psychological traits, Facebook usage, and Facebook addiction model of Taiwanese university students, Telematics and Informatics,, 31, 597, 10.1016/j.tele.2014.01.001 · DOI · Paper page
  5. Nunnally, 1978, Psychometric theory
  6. Pavlou, 2003, Consumer acceptance of electronic commerce: Integrating trust and risk with the technology acceptance model, International Journal of Electronic Commerce,, 7, 101, 10.1080/10864415.2003.11044275 · DOI · Paper page
  7. Khan, 2017, Social media engagement: What motivates user participation and consumption on YouTube?, Computers in Human Behavior,, 66,, 236, 10.1016/j.chb.2016.09.024 · DOI · Paper page
  8. Young, 1998, The relationship between depression and Internet addiction, CyberPsychology & Behavior,, 1, 25, 10.1089/cpb.1998.1.25 · DOI
  9. Sánchez-Franco, 2005, Web acceptance and usage model: A comparison between goal-directed and experiential web users, Internet Research,, 15, 21, 10.1108/10662240510577059 · DOI
  10. Balakrishnan, 2017, Validation of the YouTube Addiction Scale
  11. Cutler, 1980, Process gratification in aging cohorts, Journalism Quarterly,, 57, 269, 10.1177/107769908005700210 · DOI
  12. Caplan, 2010, Internet addiction: A handbook for evaluation and treatment, 35
  13. Balakrishnan, 2017, Validation of the YouTube Addiction Scale
  14. Park, 2016, The health-related uses and gratifications of YouTube: Motive, cognitive involvement, online activity, and sense of empowerment, Journal of Consumer Health on the Internet,, 20, 52, 10.1080/15398285.2016.1167580 · DOI
  15. Nunnally, 1978, Psychometric theory
  16. Lange, 2007c, Searching for the ‘You’ in ‘YouTube’: An analysis of online response ability, 36
  17. Lin, 1996, Looking back: The contribution of Blumler and Katz’s uses of mass communication to communication research, Journal of Broadcasting & Electronic Media,, 40, 574, 10.1080/08838159609364379 · DOI · Paper page
  18. Ryan, 2014, The uses and abuses of Facebook: A review of Facebook addiction, Journal of Behavioral Addictions,, 3, 133, 10.1556/jba.3.2014.016 · DOI · Paper page
  19. Lange, 2007, a Commenting on comments : Investigating responses to antagonism on YouTube Proceedings of the Society for Conference, Applied Anthropology
  20. Griffiths, 1999, Internet addiction: Fact or fiction?, The Psychologist: Bulletin of the British Psychological Society,, 12,, 246
  21. Kuss, 2017, Social networking sites and addiction: Ten lessons learned, International Journal of Environmental Research and Public Health,, 14, 311, 10.3390/ijerph14030311 · DOI · Paper page
  22. Rosen, 2013, Is Facebook creating “iDisorders”? The link between clinical symptoms of psychiatric disorders and technology use, attitudes and anxiety, Computers in Human Behavior,, 29, 1243, 10.1016/j.chb.2012.11.012 · DOI · Paper page
  23. Edwards, 1993, Development of a new scale for measuring compulsive buying behavior, Financial Counseling and Planning,, 4, 67
  24. Charney, 2002, Communication technology and society: Audience adoption and uses, 379
  25. Joo, 2013, Exploring Koreans’ smartphone usage: An integrated model of the technology acceptance model and uses and gratifications theory, Computers in Human Behavior,, 29, 2512, 10.1016/j.chb.2013.06.002 · DOI
  26. Chou, 2000, Internet addiction, usage, gratification, and pleasure experience: The Taiwan college students’ case, Computers & Education,, 35, 65, 10.1016/s0360-1315(00)00019-1 · DOI
  27. Olney, 1991, Consumer responses to advertising: The effects of ad content, emotions, and attitude toward the ad on viewing time, Journal of Consumer Research,, 17, 440, 10.1086/208569 · DOI
  28. Cranwell, 2015, Adolescents’ exposure to tobacco and alcohol content in YouTube music videos, Addiction,, 110, 703, 10.1111/add.12835 · DOI
  29. Korgaonkar, 2002, Web usage, advertising, and shopping: Relationship patterns, Internet Research,, 12, 191, 10.1108/10662240210422549 · DOI
  30. McCormack, 2013, An examination of participation in online gambling activities and the relationship with problem gambling, Journal of Behavioral Addictions,, 2, 31, 10.1556/jba.2.2013.1.5 · DOI
  31. Caplan, 2010, Internet addiction: A handbook for evaluation and treatment, 35
  32. Davis, 1993, User acceptance of information technology: System characteristics, user perceptions and behavioral impacts, International Journal of Man-Machine Studies,, 38, 475, 10.1006/imms.1993.1022 · DOI
  33. Andreassen, 2013, The relationships between behavioral addictions and the five-factor model of personality, Journal of Behavioral Addictions,, 2, 90, 10.1556/jba.2.2013.003 · DOI · Paper page
  34. Berger, 2012, What makes online content viral?, Journal of Marketing Research,, 49, 192, 10.1509/jmr.10.0353 · DOI · Paper page
  35. Blumler, 1974, The uses of mass communications: Current perspectives on gratifications research
  36. Leménager, 2013, Self-concept deficits in massively multiplayer online role-playing games addiction, European Addiction Research,, 19, 227, 10.1159/000345458 · DOI
  37. Mo, 2015, Exploring the roles of narcissism, uses of, and gratifications from microblogs on affinity-seeking and social capital, Asian Journal of Social Psychology,, 18, 152, 10.1111/ajsp.12087 · DOI
  38. De Vries, 2012, Popularity of brand posts on brand fan pages: An investigation of the effects of social media marketing, Journal of Interactive Marketing,, 26, 83, 10.1016/j.intmar.2012.01.003 · DOI · Paper page
  39. Chiang, 2015, YouTube stickiness: The needs, personal, and environmental perspective, Internet Research,, 25, 85, 10.1108/intr-11-2013-0236 · DOI · Paper page
  40. Prensky, 2001, Digital natives, digital immigrants (Part 1), On the Horizon,, 9, 1
  41. Sumiala, 2015, News rituals of participation: Negotiating temporalities, categories, and hierarchies of news-making on YouTube, Anthropological Notebooks,, 21, 5
  42. Flanagin, 2001, Internet use in the contemporary media environment, Human Communication Research,, 27, 153, 10.1093/hcr/27.1.153 · DOI
  43. Acar, 2016, Are Heimlich maneuver videos on YouTube accurate and reliable?, Signa Vitae,, 11, 132, 10.22514/sv111.052016.9 · DOI
  44. Burke, 2009, Work motivations, work outcomes, and health: Passion versus addiction, Journal of Business Ethics,, 84, 257, 10.1007/s10551-008-9697-0 · DOI
  45. Taylor, 2015, On the new era of zipping and zapping: The need for research on how advertisers deal with an era of time-shifted television program viewing on a variety of devices, International Journal of Advertising,, 34, 403, 10.1080/02650487.2015.1048602 · DOI
  46. Finamore, 2011, YouTube everywhere: Impact of device and infrastructure synergies on user experience, 345
  47. Baron, 1986, The moderator–mediator variable distinction in social psychological research: Conceptual, strategic, and statistical considerations, Journal of Personality and Social Psychology,, 51, 1173, 10.1037/0022-3514.51.6.1173 · DOI · Paper page
  48. Caplan, 2003, Preference for online social interaction: A theory of problematic Internet use and psychosocial well-being, Communication Research,, 30, 625, 10.1177/0093650203257842 · DOI · Paper page
  49. Haridakis, 2009, Social interaction and co-viewing with YouTube: Blending mass communication reception and social connection, Journal of Broadcasting & Electronic Media,, 53, 317, 10.1080/08838150902908270 · DOI · Paper page
  50. Gainsbury, 2013, Consumer attitudes towards Internet gambling: Perceptions of responsible gambling policies, consumer protection, and regulation of online gambling sites, Computers in Human Behavior,, 29, 235, 10.1016/j.chb.2012.08.010 · DOI
  51. Siersdorfer, 2010, How useful are your comments? Analyzing and predicting YouTube comments and comment ratings, 891
  52. Liu, 2010, Understanding Twitter usage: What drive people continue to tweet
  53. Cha, 2014, Usage of video sharing websites: Drivers and barriers, Telematics and Informatics,, 31, 16, 10.1016/j.tele.2012.01.003 · DOI
  54. Duncan, 2013, YouTube as a source of clinical skills education, Nurse Education Today,, 33, 1576, 10.1016/j.nedt.2012.12.013 · DOI
  55. Kuss, 2012, Online gaming addiction? Motives predict addictive play behavior in massively multiplayer online role-playing games, Cyberpsychology, Behavior, and Social Networking,, 15, 480, 10.1089/cyber.2012.0034 · DOI
  56. Rubin, 1983, Television uses and gratifications: The interactions of viewing patterns and motivations, Journal of Broadcasting & Electronic Media,, 27, 37, 10.1080/08838158309386471 · DOI · Paper page
  57. Weiyan, 2015, A historical overview of uses and gratifications theory, Cross-Cultural Communication,, 11, 71
  58. Preacher, 2004, SPSS and SAS procedures for estimating indirect effects in simple mediation models, Behavior Research Methods,, 36, 717, 10.3758/bf03206553 · DOI · Paper page
  59. Song, 2004, Internet gratifications and Internet addiction: On the uses and abuses of new media, CyberPsychology & Behavior,, 7, 384, 10.1089/cpb.2004.7.384 · DOI
  60. Chak, 2004, Shyness and locus of control as predictors of Internet addiction and Internet use, CyberPsychology & Behavior,, 7, 559, 10.1089/cpb.2004.7.559 · DOI
  61. Bhattacherjee, 2009, The intention–behaviour gap in technology usage: The moderating role of attitude strength, Behaviour & Information Technology,, 28, 389, 10.1080/01449290802121230 · DOI
  62. Shao, 2009, Understanding the appeal of user-generated media: A uses and gratification perspective, Internet Research,, 19, 7, 10.1108/10662240910927795 · DOI · Paper page
  63. Boyd, 2007, Social network sites: Definition, history, and scholarship, Journal of Computer-Mediated Communication,, 13, 210, 10.1111/j.1083-6101.2007.00393.x · DOI · Paper page
  64. McCormack, 2012, Motivating and inhibiting factors in online gambling behaviour: A grounded theory study, International Journal of Mental Health and Addiction,, 10, 39, 10.1007/s11469-010-9300-7 · DOI
  65. O’Keeffe, 2011, The impact of social media on children, adolescents, and families, Pediatrics,, 127, 800, 10.1542/peds.2011-0054 · DOI · Paper page
  66. Papacharissi, 2000, Predictors of Internet use, Journal of Broadcasting & Electronic Media,, 44, 175, 10.1207/s15506878jobem4402_2 · DOI · Paper page
  67. Subramani, 2003, Knowledge-sharing and influence in online social networks via viral marketing, Communications of the ACM,, 46, 300, 10.1145/953460.953514 · DOI
  68. Cranwell, 2016, Adult and adolescent exposure to tobacco and alcohol content in contemporary YouTube music videos in Great Britain: A population estimate, Journal of Epidemiology and Community Health,, 70, 488, 10.1136/jech-2015-206402 · DOI
  69. Palmgreen, 1979, Uses and gratifications and exposure to public television: A discrepancy approach, Communication Research,, 6, 155, 10.1177/009365027900600203 · DOI · Paper page
  70. Venkatesh, 2000, Determinants of perceived ease of use: Integrating control, intrinsic motivation, and emotion into the technology acceptance model, Information Systems Research,, 11, 342, 10.1287/isre.11.4.342.11872 · DOI · Paper page
  71. Gill, 2007, Youtube traffic characterization: A view from the edge, 15
  72. Shaw, 2002, In defense of the Internet: The relationship between Internet communication and depression, loneliness, self-esteem, and perceived social support, CyberPsychology & Behavior,, 5, 157, 10.1089/109493102753770552 · DOI · Paper page
  73. Lee, 2013, User acceptance of YouTube for procedural learning: An extension of the technology acceptance model, Computers & Education,, 61, 193, 10.1016/j.compedu.2012.10.001 · DOI · Paper page
  74. Moor, 2010, Flaming on YouTube, Computers in Human Behavior,, 26, 1536, 10.1016/j.chb.2010.05.023 · DOI
  75. Yee, 2006, Motivations for play in online games, CyberPsychology & Behavior,, 9, 772, 10.1089/cpb.2006.9.772 · DOI
  76. Andreassen, 2012, Development of a Facebook Addiction Scale, Psychological Reports,, 110, 501, 10.2466/02.09.18.pr0.110.2.501-517 · DOI · Paper page
  77. Lin, 1999, Online service adoption likelihood, Journal of Advertising Research,, 39,, 79
  78. Kim, 2013, The influence of an educational course on language expression and treatment of gaming addiction for massive multiplayer online role-playing game (MMORPG) players, Computers & Education,, 63,, 208, 10.1016/j.compedu.2012.12.008 · DOI
  79. Lange, 2007b, Publicly private and privately public: Social networking on YouTube, Journal of Computer-Mediated Communication,, 13, 361, 10.1111/j.1083-6101.2007.00400.x · DOI
  80. Venkatesh, 2000, A theoretical extension of the technology acceptance model: Four longitudinal field studies, Management Science,, 46, 186, 10.1287/mnsc.46.2.186.11926 · DOI · Paper page
  81. Huang, 2016, 100 million views of electronic cigarette YouTube videos and counting: Quantification, content evaluation, and engagement levels of videos, Journal of Medical Internet Research,, 18, e67, 10.2196/jmir.4265 · DOI
  82. Uysal, 2013, Mediating effect of Facebook® addiction on the relationship between subjective vitality and subjective happiness, Psychological Reports,, 113, 948, 10.2466/02.09.18.pr0.113x32z3 · DOI
  83. Ji, 2013, Love Internet, love online content: Predicting Internet affinity with information gratification and social gratifications, Internet Research,, 23, 396, 10.1108/intr-08-2012-0155 · DOI
  84. Venkatesh, 2003, User acceptance of information technology: Toward a unified view, MIS Quarterly,, 27, 425, 10.2307/30036540 · DOI · Paper page
  85. Ferris, 2001, Social ramifications of excessive Internet use among college-age males, Journal of Technology and Culture,, 20, 44
  86. Beranuy, 2013, A qualitative analysis of online gaming addicts in treatment, International Journal of Mental Health and Addiction,, 11, 149, 10.1007/s11469-012-9405-2 · DOI
  87. Ruggiero, 2000, Uses and gratifications theory in the 21st century, Mass Communication and Society,, 3, 3, 10.1207/s15327825mcs0301_02 · DOI · Paper page
  88. Ferris, 2001, Social ramifications of excessive Internet use among college-age males, Journal of Technology and Culture,, 20, 44
  89. Stafford, 2004, Determining uses and gratifications for the Internet, Decision Sciences,, 35, 259, 10.1111/j.00117315.2004.02524.x · DOI · Paper page
  90. Lu, 2010, Information sharing behaviour on blogs in Taiwan: Effects of interactivities and gender differences, Journal of Information Science,, 36, 401, 10.1177/0165551510363631 · DOI
  91. Griffiths, 2005, A ‘components’ model of addiction within a biopsychosocial framework, Journal of Substance Use,, 10, 191, 10.1080/14659890500114359 · DOI · Paper page
  92. Raacke, 2008, MySpace and Facebook: Applying the uses and gratifications theory to exploring friend-networking sites, CyberPsychology & Behavior,, 11, 169, 10.1089/cpb.2007.0056 · DOI · Paper page
  93. Bennett, 2008, The ‘digital natives’ debate: A critical review of the evidence, British Journal of Educational Technology,, 39, 775, 10.1111/j.1467-8535.2007.00793.x · DOI · Paper page
  94. Kuo, 2013, Relationships among community interaction characteristics, perceived benefits, community commitment, and oppositional brand loyalty in online brand communities, International Journal of Information Management,, 33, 948, 10.1016/j.ijinfomgt.2013.08.005 · DOI
  95. Elliott, 1987, The 1985 Philadelphia newspaper strike: A uses and gratifications study, Journalism Quarterly,, 64, 679, 10.1177/107769908706400401 · DOI
  96. Peters, 2007, An exploratory investigation of consumers’ perceptions of wireless advertising, Journal of Advertising,, 36, 129, 10.2753/joa0091-3367360410 · DOI
  97. Williams, 1988, Research methods and the new media
  98. Wesner, 2008, Boomers and millennials have much in common, Organization Development Journal,, 26, 89
  99. Lortie, 2013, Internet addiction assessment tools: Dimensional structure and methodological status, Addiction,, 108, 1207, 10.1111/add.12202 · DOI
  100. Bakar, 2014, Factors of gratification contributing in continuance intention to watch movies on YouTube, Procedia – Social and Behavioral Sciences,, 155,, 9, 10.1016/j.sbspro.2014.10.248 · DOI

Cited by

Sorted by citations

Items 201–265 of 265

Related

See all

Metadata

Authors
Balakrishnan, J., & Griffiths, M. D.
Affiliations
  • 1 Thiagarajar School of Management, Madurai, India
  • Nottingham Trent University (GB)
Corresponding author
Griffiths, Mark D.
ORCID
Venue
Journal of Behavioral Addictions
Publisher
Akademiai Kiado Zrt.
Published
2017-09
Volume
6
Issue
3
Pages
364-377
ISSN
  • 2062-5871 (ISSN-L)
  • 2063-5303
DOI
10.1556/2006.6.2017.058
PMC
PMC5700732
OpenAlex
W2756435224
Semantic Scholar
629959749148f00bf1de3dc53f7a04d8f50912ba
Cited by
266
References
96
Citations by year
2026: 12 · 2025: 24 · 2024: 37 · 2023: 45 · 2022: 58 · 2021: 46 · 2020: 24 · 2019: 10 · 2018: 10
FWCI
30.82
Type
journal article
Language
en
Open access
Locations
  • Journal of Behavioral Addictions (publishedVersion)
  • PubMed Central (publishedVersion, cc-by-nc)
  • PubMed (publishedVersion)
  • Nottingham Trent University's Institutional Repository (Nottingham Trent Repository) (acceptedVersion)
  • Repository of the Academy's Library (Library of the Hungarian Academy of Sciences) (acceptedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Impact of Technology on Adolescents
  • Social Sciences › Communication › Media and Digital Communication
  • Social Sciences › Decision Sciences › Information Systems and Management › Technology Adoption and User Behaviour
Keywords
social media addiction, content creation, user gratification, social gratification, online video platforms
MeSH terms
Adolescent, Adult, Communication, Female, Humans, Male, Models, Psychological, Surveys and Questionnaires, Reward, Social Behavior, Students, Video Recording, Multivariate Analysis, Likelihood Functions, Behavior, Addictive, Young Adult, Social Media

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

A language model drew the claims from the paper on 2026-10-09, under version 3 of the claim definition (model deepseek-v4.1-flash, prompt extract-v3).

A second model labelled each claim on 2026-10-09 (model jev-1.13-20260917, definition revision gold-guideline-v0.2).

Statistics and arithmetic are recomputed, not judged.

Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.

What counts as a claim ›How we measure confidence ›How we check this ›

Are you an author, or do you see a problem with this page? Request a review