IDEAS home Printed from https://ideas.repec.org/a/pal/palcom/v9y2022i1d10.1057_s41599-022-01352-9.html
   My bibliography  Save this article

Modeling narrative features in TV series: coding and clustering analysis

Author

Listed:
  • Marta Rocchi

    (Alma Mater Studiorum–University of Bologna)

  • Guglielmo Pescatore

    (Alma Mater Studiorum–University of Bologna)

Abstract

TV series have gained both economic and cultural relevance. Their development over time can hardly be traced back to the simple programmatic action of creative intentionality. Instead, TV series might be studied as narrative ecosystems with emergent trends and patterns. This paper aims to boost quantitative research in the field of media studies, first considering a comparative and data-driven study of the narrative features in the US medical TV series, one of the most popular and longest-running genres on global television. Based on a corpus of more than 400 h of video, we investigate the storytelling evolution of eight audiovisual serial products by identifying three main narrative features (i.e., isotopies). The implemented schematization allows to grasp the basic components of the social interactions showing the strength of the medical genre and its ability to rebuild, in its microcosm, the essential traits of the human macrocosm where random everyday life elements (seen in the medical cases plot) mix and overlap with working and social relationships (professional plot) and personal relationships (sentimental plot). This study relies on data-driven research that combines content analysis and clustering analysis. It significantly differs from traditional studies regarding the narrative features of medical dramas and broadly the field of television studies. We proved that the three isotopies are good descriptors for the medical drama genre and identified four narrative profiles which emphasize the strong stability of these serial products. Contrary to what is often taken for granted in many interpretative studies, creative decisions rarely significantly change the general narrative aspects of the wider series.

Suggested Citation

  • Marta Rocchi & Guglielmo Pescatore, 2022. "Modeling narrative features in TV series: coding and clustering analysis," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-11, December.
  • Handle: RePEc:pal:palcom:v:9:y:2022:i:1:d:10.1057_s41599-022-01352-9
    DOI: 10.1057/s41599-022-01352-9
    as

    Download full text from publisher

    File URL: http://link.springer.com/10.1057/s41599-022-01352-9
    File Function: Abstract
    Download Restriction: Access to full text is restricted to subscribers.

    File URL: https://libkey.io/10.1057/s41599-022-01352-9?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. Brock, Guy & Pihur, Vasyl & Datta, Susmita & Datta, Somnath, 2008. "clValid: An R Package for Cluster Validation," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 25(i04).
    2. Hennig, Christian, 2007. "Cluster-wise assessment of cluster stability," Computational Statistics & Data Analysis, Elsevier, vol. 52(1), pages 258-271, September.
    3. Charrad, Malika & Ghazzali, Nadia & Boiteau, Véronique & Niknafs, Azam, 2014. "NbClust: An R Package for Determining the Relevant Number of Clusters in a Data Set," Journal of Statistical Software, Foundation for Open Access Statistics, vol. 61(i06).
    4. Kassarjian, Harold H, 1977. "Content Analysis in Consumer Research," Journal of Consumer Research, Journal of Consumer Research Inc., vol. 4(1), pages 8-18, June.
    5. Hennig, Christian, 2008. "Dissolution point and isolation robustness: Robustness criteria for general cluster analysis methods," Journal of Multivariate Analysis, Elsevier, vol. 99(6), pages 1154-1176, July.
    Full references (including those not matched with items on IDEAS)

    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. Ana Alina Tudoran, 2022. "A machine learning approach to identifying decision-making styles for managing customer relationships," Electronic Markets, Springer;IIM University of St. Gallen, vol. 32(1), pages 351-374, March.
    2. Wu, Han-Ming, 2011. "On biological validity indices for soft clustering algorithms for gene expression data," Computational Statistics & Data Analysis, Elsevier, vol. 55(5), pages 1969-1979, May.
    3. Wu, Tong & Rocha, Juan C. & Berry, Kevin & Chaigneau, Tomas & Hamann, Maike & Lindkvist, Emilie & Qiu, Jiangxiao & Schill, Caroline & Shepon, Alon & Crépin, Anne-Sophie & Folke, Carl, 2024. "Triple Bottom Line or Trilemma? Global Tradeoffs Between Prosperity, Inequality, and the Environment," World Development, Elsevier, vol. 178(C).
    4. Sara Dolnicar & Friedrich Leisch, 2017. "Using segment level stability to select target segments in data-driven market segmentation studies," Marketing Letters, Springer, vol. 28(3), pages 423-436, September.
    5. Nikolaos Karapetsas & Thomas K. Alexandridis & George Bilas & Serafeim Theocharis & Stefanos Koundouras, 2023. "Delineating Natural Terroir Units in Wine Regions Using Geoinformatics," Agriculture, MDPI, vol. 13(3), pages 1-18, March.
    6. Aicha Ait Sair & Kamal Kansou & Franck Michaud & Bernard Cathala, 2021. "Multicriteria Definition of Small-Scale Biorefineries Based on a Statistical Classification," Sustainability, MDPI, vol. 13(13), pages 1-18, June.
    7. Hsu, David, 2015. "Comparison of integrated clustering methods for accurate and stable prediction of building energy consumption data," Applied Energy, Elsevier, vol. 160(C), pages 153-163.
    8. Borke, Lukas & Härdle, Wolfgang Karl, 2017. "GitHub API based QuantNet Mining infrastructure in R," SFB 649 Discussion Papers 2017-008, Humboldt University Berlin, Collaborative Research Center 649: Economic Risk.
    9. Anastasia Panori, 2017. "A Tale of Hidden Cities," REGION, European Regional Science Association, vol. 4, pages 19-38.
    10. repec:hum:wpaper:sfb649dp2017-008 is not listed on IDEAS
    11. Daly, Bonita A. & Schuler, Drue K., 1998. "Redefining a certified public accounting firm," Accounting, Organizations and Society, Elsevier, vol. 23(5-6), pages 549-567.
    12. Patrick Zschech & Kai Heinrich & Raphael Bink & Janis S. Neufeld, 2019. "Prognostic Model Development with Missing Labels," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 61(3), pages 327-343, June.
    13. Sirieix, Lucie & Lála, Jan & Kocmanová, Klára, 2017. "Understanding the antecedents of consumers' attitudes towards doggy bags in restaurants: Concern about food waste, culture, norms and emotions," Journal of Retailing and Consumer Services, Elsevier, vol. 34(C), pages 153-158.
    14. Chiara Mauri & Angelo Di Gregorio & Alice Mazzucchelli & Isabella Maggioni, 2017. "The employability of marketing graduates in the era of digitalisation and globalisation," MERCATI & COMPETITIVIT?, FrancoAngeli Editore, vol. 2017(4), pages 103-124.
    15. Bolívar, Fernando & Duran, Miguel A. & Lozano-Vivas, Ana, 2023. "Bank business models, size, and profitability," Finance Research Letters, Elsevier, vol. 53(C).
    16. Tino Werner, 2023. "Quantitative robustness of instance ranking problems," Annals of the Institute of Statistical Mathematics, Springer;The Institute of Statistical Mathematics, vol. 75(2), pages 335-368, April.
    17. Ki, Chung-Wha (Chloe) & Cuevas, Leslie M. & Chong, Sze Man & Lim, Heejin, 2020. "Influencer marketing: Social media influencers as human brands attaching to followers and yielding positive marketing results by fulfilling needs," Journal of Retailing and Consumer Services, Elsevier, vol. 55(C).
    18. Martin Berner & Jino Augustine & Alexander Maedche, 2016. "The Impact of Process Visibility on Process Performance," Business & Information Systems Engineering: The International Journal of WIRTSCHAFTSINFORMATIK, Springer;Gesellschaft für Informatik e.V. (GI), vol. 58(1), pages 31-42, February.
    19. Gainbi Park & Zengwang Xu, 2022. "The constituent components and local indicator variables of social vulnerability index," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 110(1), pages 95-120, January.
    20. Roopam Shukla & Ankit Agarwal & Kamna Sachdeva & Juergen Kurths & P. K. Joshi, 2019. "Climate change perception: an analysis of climate change and risk perceptions among farmer types of Indian Western Himalayas," Climatic Change, Springer, vol. 152(1), pages 103-119, January.
    21. Pullig, Chris & Maxham, James III & Hair, Joseph Jr., 2002. "Salesforce automation systems: an exploratory examination of organizational factors associated with effective implementation and salesforce productivity," Journal of Business Research, Elsevier, vol. 55(5), pages 401-415, May.

    More about this item

    Statistics

    Access and download statistics

    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:pal:palcom:v:9:y:2022:i:1:d:10.1057_s41599-022-01352-9. 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: Sonal Shukla or Springer Nature Abstracting and Indexing (email available below). General contact details of provider: https://www.nature.com/ .

    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.