Multimedia Tools and Applications

, Volume 78, Issue 3, pp 3321–3339 | Cite as

A combined approach for the analysis of support groups on Facebook - the case of patients of hidradenitis suppurativa

  • Gianfranco LombardoEmail author
  • Paolo Fornacciari
  • Monica Mordonini
  • Laura Sani
  • Michele Tomaiuolo


Hidradenitis Suppurativa (HS), also known as Acne Inversa, is a chronic, underdiagnosed, often debilitating and painful disease that affects the folds of the skin. It has a considerable negative impact on the quality of life and on the emotional well-being. In this paper we discuss some results obtained by applying automatic Emotion Detection and Social Network Analysis techniques on the Facebook group of the Italian patients’ association (Inversa Onlus). In particular, we analyze the patients’ emotional states, as expressed by the posts and comments published from 2009 to 2017, and how these emotions are influenced by different social network factors, such as interactions and friendships in the group, during the observed years.


Social network analysis Emotion detection Sentiment analysis Hidradenitis suppurativa Facebook 



  1. 1.
    Addis A, Armano G, Vargiu E (2008) A progressive filtering approach to hierarchical text categorization. Communications of SIWN 5:28–32Google Scholar
  2. 2.
    Angiani G, Cagnoni S, Chuzhikova N, Fornacciari P, Mordonini M, Tomaiuolo M (2016) Flat and hierarchical classifiers for detecting emotion in tweets AI* IA 2016 Advances in artificial intelligence, pp 51–64. SpringerGoogle Scholar
  3. 3.
    Angiani G, Fornacciari P, Iotti E, Mordonini M, Tomaiuolo M (2016) Models of participation in social networks. Social Media Performance Evaluation and Success Measurements, pp 196Google Scholar
  4. 4.
    Bettoli V, Pasquinucci S, Caracciolo S, Piccolo D, Cazzaniga S, Fantini F, Binello L, Pintori G, Naldi L (2016) The hidradenitis suppurativa patient journey in italy: current status, unmet needs and opportunities. J Eur Acad Dermatol Venereol 30(11):1965–1970Google Scholar
  5. 5.
    Chen J, Huang H, Tian S, Qu Y (2009) Feature selection for text classification with naïve bayes. Expert Systems with Applications 36(3, Part 1):5432–5435. CrossRefGoogle Scholar
  6. 6.
    Dumais S, Chen H (2000) Hierarchical classification of web content. In: Proceedings of the 23rd annual international ACM SIGIR conference on Research and development in information retrieval, pp 256–263. ACMGoogle Scholar
  7. 7.
    Franchi E, Poggi A, Tomaiuolo M (2016) Social media for online collaboration in firms and organizations. International Journal of Information System Modeling and Design (IJISMD) 7(1):18–31CrossRefGoogle Scholar
  8. 8.
    Ghazi D, Inkpen D, Szpakowicz S (2010) Hierarchical approach to emotion recognition and classification in texts. Advances in Artificial Intelligence 6085:40–50Google Scholar
  9. 9.
    Greaves F, Ramirez-Cano D, Millett C, Darzi A, Donaldson L (2013) Harnessing the cloud of patient experience: using social media to detect poor quality healthcare. BMJ Qual Saf 22(3):251– 255CrossRefGoogle Scholar
  10. 10.
    Greene JA, Choudhry NK, Kilabuk E, Shrank WH (2011) Online social networking by patients with diabetes: a qualitative evaluation of communication with facebook. J Gen Intern Med 26(3):287– 292CrossRefGoogle Scholar
  11. 11.
    Huang X, Zhang L, Liu T, Chiu D, Zhu T, Li X (2014) Detecting suicidal ideation in chinese microblogs with psychological lexicons. In: 2014 IEEE 11th Intl Conf on Ubiquitous Intelligence and Computing and 2014 IEEE 11th Intl Conf on Autonomic and Trusted Computing and 2014 IEEE 14th Intl Conf on Scalable Computing and Communications and Its Associated Workshops pp 844– 849Google Scholar
  12. 12.
    Kao ECC, Liu CC, Yang TH, Hsieh CT, Soo VW (2009) Towards text-based emotion detection a survey and possible improvements. In: Information management and engineering, 2009. ICIME’09. International conference on, pp 70–74. IEEEGoogle Scholar
  13. 13.
    Liu B (2012) Sentiment analysis and opinion mining. Synthesis lectures on human language technologies 5(1):1–167CrossRefGoogle Scholar
  14. 14.
    Lombardo G, Ferrari A, Fornacciari P, Mordonini M, Sani L, Tomaiuolo M (2018) Dynamics of emotions and relations in a facebook group of patients with hidradenitis suppurativa. pp 269–278Google Scholar
  15. 15.
    Maddali HT, Gloor PA, Margolis PA (2015) Comparing online community structure of patients of chronic diseases. CoRR arXiv:1502.05263
  16. 16.
    Mohammad SM (2015) Sentiment analysis: Detecting valence, emotions, and other affectual states from text. Emotion Measurement:201–238Google Scholar
  17. 17.
    Onderdijk A, Van der Zee H, Esmann S, Lophaven S, Dufour D, Jemec G, Boer J (2013) Depression in patients with hidradenitis suppurativa. J Eur Acad Dermatol Venereol 27(4):473–478CrossRefGoogle Scholar
  18. 18.
    Parrott WG (2001) Emotions in social psychology: Essential readings Psychology PressGoogle Scholar
  19. 19.
    Roccetti M, Marfia G, Salomoni P, Prandi C, Zagari RM, Kengni FLG, Bazzoli F, Montagnani M (2017) Attitudes of crohn’s disease patients: Infodemiology case study and sentiment analysis of facebook and twitter posts. In: JMIR Public health and surveillanceGoogle Scholar
  20. 20.
    Sani L, Lombardo G, Pecori R, Fornacciari P, Mordonini M, Cagnoni S (2018) Social relevance index for studying communities in a facebook group of patients. In: Sim K., Kaufmann P. (eds) Applications of evolutionary computation. Springer International Publishing, Cham, pp 125–140Google Scholar
  21. 21.
    Silla Jr CN, Freitas AA (2011) A survey of hierarchical classification across different application domains. Data Min Knowl Disc 22(1-2):31–72MathSciNetCrossRefGoogle Scholar
  22. 22.
    Wang X, Zhang C, Ji Y, Sun L, Wu L, Bao Z (2013) A depression detection model based on sentiment analysis in micro-blog social network. In: Li J, Cao L, Wang C, Tan KC, Liu B, Pei J, Tseng VS (eds) Trends and applications in knowledge discovery and data mining. Springer, Berlin, pp 201– 213Google Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2018

Authors and Affiliations

  1. 1.Dipartimento di Ingegneria e ArchitetturaUniversità di ParmaParmaItaly

Personalised recommendations