IDEAS home Printed from https://ideas.repec.org/a/eee/phsmap/v535y2019ics0378437119313597.html
   My bibliography  Save this article

A new direction in social network analysis: Online social network analysis problems and applications

Author

Listed:
  • Can, Umit
  • Alatas, Bilal

Abstract

The use of online social networks has made significant progress in recent years as the use of the Internet has become widespread worldwide as the technological infrastructure and the use of technological products evolve. It has become more suitable to reach online social networking sites such as Facebook, Twitter, Instagram and LinkedIn via the internet and web 3.0 technologies. Thus, people have shared their views on many different topics and their emotions with other users more widely on these platforms. This means that a huge amount of data is created on platforms where millions of people connect with each other through social networks. Nevertheless, the development of computational paradigms at high speed and complexity with technological possibilities allows analysis of valuable data by means of social network analysis methods. Our goal for this paper is to present a review of novel and popular online social network analysis problems with related applications and a reference work for researchers interested in analyzing online social network data and social network problems. Unlike other individual studies we have gathered 21 online social network problems and defined them with related studies. Thus, this study is original by presenting an important source of research by explaining the problems of online social network and the studies performed in this area.

Suggested Citation

  • Can, Umit & Alatas, Bilal, 2019. "A new direction in social network analysis: Online social network analysis problems and applications," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 535(C).
    • Handle: RePEc:eee:phsmap:v:535:y:2019:i:c:s0378437119313597
    DOI: 10.1016/j.physa.2019.122372
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0378437119313597
    Download Restriction: Full text for ScienceDirect subscribers only. Journal offers the option of making the article available online on Science direct for a fee of $3,000
    File URL: https://libkey.io/10.1016/j.physa.2019.122372?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Nam P Nguyen & Thang N Dinh & Yilin Shen & My T Thai, 2014. "Dynamic Social Community Detection and Its Applications," PLOS ONE, Public Library of Science, vol. 9(4), pages 1-18, April.
    2. Zavala, Araceli & Ramirez-Marquez, Jose Emmanuel, 2019. "Visual analytics for identifying product disruptions and effects via social media," International Journal of Production Economics, Elsevier, vol. 208(C), pages 544-559.
    3. Zoey Chen & Jonah Berger, 2013. "When, Why, and How Controversy Causes Conversation," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 40(3), pages 580-593.
    4. Cho, Youngsang & Hwang, Junseok & Lee, Daeho, 2012. "Identification of effective opinion leaders in the diffusion of technological innovation: A social network approach," Technological Forecasting and Social Change, Elsevier, vol. 79(1), pages 97-106.
    5. Fan, W. & Yeung, K.H., 2011. "Online social networks—Paradise of computer viruses," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 390(2), pages 189-197.
    6. Victor W. Chu & Raymond K. Wong & Chi-Hung Chi, 2012. "Over-Fitting and Error Detection for Online Role Mining," International Journal of Web Services Research (IJWSR), IGI Global, vol. 9(4), pages 1-23, October.
    7. Xiong, Feng & Chapple, Larelle & Yin, Haiying, 2018. "The use of social media to detect corporate fraud: A case study approach," Business Horizons, Elsevier, vol. 61(4), pages 623-633.
    8. Johansson, Tobias, 2017. "Gossip spread in social network Models," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 471(C), pages 126-134.
    9. Siganos, Antonios & Vagenas-Nanos, Evangelos & Verwijmeren, Patrick, 2014. "Facebook's daily sentiment and international stock markets," Journal of Economic Behavior & Organization, Elsevier, vol. 107(PB), pages 730-743.
    10. Lin, Hsin-Chen & Bruning, Patrick F. & Swarna, Hepsi, 2018. "Using online opinion leaders to promote the hedonic and utilitarian value of products and services," Business Horizons, Elsevier, vol. 61(3), pages 431-442.
    11. Nicky J. Welton & Howard H. Z. Thom, 2015. "Value of Information," Medical Decision Making, , vol. 35(5), pages 564-566, July.
    12. Wang, Kai-Yu & Ting, I-Hsien & Wu, Hui-Ju, 2013. "Discovering interest groups for marketing in virtual communities: An integrated approach," Journal of Business Research, Elsevier, vol. 66(9), pages 1360-1366.
    13. Chujie Tian & Jian Ma & Chunhong Zhang & Panpan Zhan, 2018. "A Deep Neural Network Model for Short-Term Load Forecast Based on Long Short-Term Memory Network and Convolutional Neural Network," Energies, MDPI, vol. 11(12), pages 1-13, December.
    14. Tsapeli, Fani & Musolesi, Mirco & Tino, Peter, 2017. "Non-parametric causality detection: An application to social media and financial data," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 483(C), pages 139-155.
    15. Umit Can & Bilal Alatas, 2017. "Big Social Network Data and Sustainable Economic Development," Sustainability, MDPI, vol. 9(11), pages 1-19, November.
    16. Jia, Peng & Liu, Jiayong & Fang, Yong & Liu, Liang & Liu, Luping, 2018. "Modeling and analyzing malware propagation in social networks with heterogeneous infection rates," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 507(C), pages 240-254.
    17. Robert M. Bond & Christopher J. Fariss & Jason J. Jones & Adam D. I. Kramer & Cameron Marlow & Jaime E. Settle & James H. Fowler, 2012. "A 61-million-person experiment in social influence and political mobilization," Nature, Nature, vol. 489(7415), pages 295-298, September.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Jing Tao & Wuliyasu Bai & Rongsheng Peng & Ziying Wu, 2024. "Sustainable Regional Straw Utilization: Collaborative Approaches and Network Optimization," Sustainability, MDPI, vol. 16(4), pages 1-23, February.
    2. Saad Awadh Alanazi & Ayesha Khaliq & Fahad Ahmad & Nasser Alshammari & Iftikhar Hussain & Muhammad Azam Zia & Madallah Alruwaili & Alanazi Rayan & Ahmed Alsayat & Salman Afsar, 2022. "Public’s Mental Health Monitoring via Sentimental Analysis of Financial Text Using Machine Learning Techniques," IJERPH, MDPI, vol. 19(15), pages 1-27, August.
    3. Ladislav Pilař & Lucie Kvasničková Stanislavská & Jana Pitrová & Igor Krejčí & Ivana Tichá & Martina Chalupová, 2019. "Twitter Analysis of Global Communication in the Field of Sustainability," Sustainability, MDPI, vol. 11(24), pages 1-16, December.
    4. Can, Umit & Alatas, Bilal, 2021. "A novel approach for efficient stance detection in online social networks with metaheuristic optimization," Technology in Society, Elsevier, vol. 64(C).
    5. Gao, Wei & Baskonus, Haci Mehmet, 2022. "Deeper investigation of modified epidemiological computer virus model containing the Caputo operator," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    6. Jabari Lotf, Jalil & Abdollahi Azgomi, Mohammad & Ebrahimi Dishabi, Mohammad Reza, 2022. "An improved influence maximization method for social networks based on genetic algorithm," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 586(C).
    7. Yuan Yuan & Xintong Sun & Ning Liu, 2022. "Measuring structural characteristics and evolutionary patterns of an industrial carbon footprint network: A social network analysis approach," Regional Science Policy & Practice, Wiley Blackwell, vol. 14(S2), pages 159-180, November.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Muller, Eitan & Peres, Renana, 2019. "The effect of social networks structure on innovation performance: A review and directions for research," International Journal of Research in Marketing, Elsevier, vol. 36(1), pages 3-19.
    2. Farivar, Samira & Wang, Fang, 2022. "Effective influencer marketing: A social identity perspective," Journal of Retailing and Consumer Services, Elsevier, vol. 67(C).
    3. Daniel Röchert & Manuel Cargnino & German Neubaum, 2022. "Two sides of the same leader: an agent-based model to analyze the effect of ambivalent opinion leaders in social networks," Journal of Computational Social Science, Springer, vol. 5(2), pages 1159-1205, November.
    4. Lin, Hsin-Chen & Bruning, Patrick F., 2024. "Guidelines for sponsorship signaling within socially complex markets," Business Horizons, Elsevier, vol. 67(1), pages 19-30.
    5. Vincenzo Varriale & Antonello Cammarano & Francesca Michelino & Mauro Caputo, 2021. "Sustainable Supply Chains with Blockchain, IoT and RFID: A Simulation on Order Management," Sustainability, MDPI, vol. 13(11), pages 1-23, June.
    6. Valeria Costantini & Francesco Crespi & Giovanni Marin & Elena Paglialunga, 2016. "Eco-innovation, sustainable supply chains and environmental performance in European industries," LEM Papers Series 2016/19, Laboratory of Economics and Management (LEM), Sant'Anna School of Advanced Studies, Pisa, Italy.
    7. Lee, Alice J. & Ames, Daniel R., 2017. "“I can’t pay more” versus “It’s not worth more”: Divergent effects of constraint and disparagement rationales in negotiations," Organizational Behavior and Human Decision Processes, Elsevier, vol. 141(C), pages 16-28.
    8. Hussain, Hadia & Murtaza, Murtaza & Ajmal, Areeb & Ahmed, Afreen & Khan, Muhammad Ovais Khalid, 2020. "A study on the effects of social media advertisement on consumer’s attitude and customer response," MPRA Paper 104675, University Library of Munich, Germany.
    9. A. G. Fatullayev & Nizami A. Gasilov & Şahin Emrah Amrahov, 2019. "Numerical solution of linear inhomogeneous fuzzy delay differential equations," Fuzzy Optimization and Decision Making, Springer, vol. 18(3), pages 315-326, September.
    10. Cyril Chalendard, 2015. "Use of internal information, external information acquisition and customs underreporting," Working Papers halshs-01179445, HAL.
    11. Schmidt, Christoph G. & Wuttke, David A. & Heese, H. Sebastian & Wagner, Stephan M., 2023. "Antecedents of public reactions to supply chain glitches," International Journal of Production Economics, Elsevier, vol. 259(C).
    12. Arun Advani & William Elming & Jonathan Shaw, 2023. "The Dynamic Effects of Tax Audits," The Review of Economics and Statistics, MIT Press, vol. 105(3), pages 545-561, May.
    13. Philippe Aghion & Ufuk Akcigit & Matthieu Lequien & Stefanie Stantcheva, 2017. "Tax simplicity and heterogeneous learning," CEP Discussion Papers dp1516, Centre for Economic Performance, LSE.
    14. Marie Bjørneby & Annette Alstadsæter & Kjetil Telle, 2018. "Collusive tax evasion by employers and employees. Evidence from a randomized fi eld experiment in Norway," Discussion Papers 891, Statistics Norway, Research Department.
    15. Chuangen Gao & Shuyang Gu & Jiguo Yu & Hai Du & Weili Wu, 2022. "Adaptive seeding for profit maximization in social networks," Journal of Global Optimization, Springer, vol. 82(2), pages 413-432, February.
    16. Koessler, Frederic & Laclau, Marie & Renault, Jérôme & Tomala, Tristan, 2022. "Long information design," Theoretical Economics, Econometric Society, vol. 17(2), May.
    17. Jamal El-Den & Pratap Adikhari & Pratap Adikhari, 2017. "Social media in the service of social entrepreneurship: Identifying factors for better services," Journal of Advances in Humanities and Social Sciences, Dr. Yi-Hsing Hsieh, vol. 3(2), pages 105-114.
    18. Annette Alstadsæter & Wojciech Kopczuk & Kjetil Telle, 2019. "Social networks and tax avoidance: evidence from a well-defined Norwegian tax shelter," International Tax and Public Finance, Springer;International Institute of Public Finance, vol. 26(6), pages 1291-1328, December.
    19. Xiongnan Jin & Sejin Chun & Jooik Jung & Kyong-Ho Lee, 0. "A fast and scalable approach for IoT service selection based on a physical service model," Information Systems Frontiers, Springer, vol. 0, pages 1-16.
    20. Jun Hong Park & Sang Ho Kook & Hyeonu Im & Soomin Eum & Chulung Lee, 2018. "Fabless Semiconductor Firms’ Financial Performance Determinant Factors: Product Platform Efficiency and Technological Capability," Sustainability, MDPI, vol. 10(10), pages 1-22, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:phsmap:v:535:y:2019:i:c:s0378437119313597. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/physica-a-statistical-mechpplications/ .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.