Mining Facebook Data of People with Rare Diseases

Reguera, Natalia; Subirats, Laia; Armayones, Manuel

doi:10.1109/cbms.2017.124

Cited by 5 publications

(1 citation statement)

References 17 publications

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“…Another interesting research study is [ 4 ], in which the authors states that, although health professionals use social media to gather information, they are skeptical of their value in communicating with patients. The current work is an extension of the preliminary analysis described in [ 5 ], which characterizes posts of the Spanish Federation of Rare Diseases (FEDER in Spanish). We found that the decalogue should focus more on help, life, people and children and less on disability, professionals and diseases.…”

Section: Introductionmentioning

confidence: 99%

Mining Facebook Data of People with Rare Diseases: A Content-Based and Temporal Analysis

Subirats

Reguera

Bañón

et al. 2018

IJERPH

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This research characterized how Facebook deals with rare diseases. This characterization included a content-based and temporal analysis, and its purpose was to help users interested in rare diseases to maximize the engagement of their posts and to help rare diseases organizations to align their priorities with the interests expressed in social networks. This research used Netvizz to download Facebook data, word clouds in R for text mining, a log-likelihood measure in R to compare texts and TextBlob Python library for sentiment analysis. The Facebook analysis shows that posts with photos and positive comments have the highest engagement. We also observed that words related to diseases, attention, disability and services have a lot of presence in the decalogue of priorities (which serves for all associations to work on the same objectives and provides the lines of action to be followed by political decision makers) and little on Facebook, and words of gratitude are more present on Facebook than in the decalogue. Finally, the temporal analysis shows that there is a high variation between the polarity average and the hour of the day.

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Section: Introductionmentioning

confidence: 99%

Mining Facebook Data of People with Rare Diseases: A Content-Based and Temporal Analysis

Subirats

Reguera

Bañón

et al. 2018

IJERPH

Self Cite

View full text Add to dashboard Cite

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Looking for Emergent Systems in Computer-Based Medical Systems: A Review from the Last Decade

Silva

Antônio

Fornazin

et al. 2019

2019 IEEE 32nd International Symposium on Computer-Based Medical Systems (CBMS)

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E-public Relations in Health Organizations: How EURORDIS-Rare Diseases Europe Uses the Website and Facebook to Communicate with Key Publics

Belim

2020

Ro. J. Comm. & PR

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This article focuses on how EURORDIS-Rare Diseases Europe uses e-Public Relations to communicate and construct and strengthen relations with key publics, concretely the patients/members and journalists. Grounded on rhetorical theory and on a triple (qualitative, quantitative, and rhetorical) analysis to content, the study explores the website, Facebook page and press releases of EURORDIS. The results show that the EURORDIS’ website encompasses six types of content: information, clarification, personalization, support, appeal, and empowerment. In Facebook (N=160), the most significant issue is “reference of an event promoted by EURORDIS” (59,4%), “information and appeal” (40,0%) is the most used content type, and “text and photo” (77,5%) is the preferable resource used. Among the rhetorical devices (N=103), the most frequent is “use of question”. The other rhetorical devices used are repetition, mix of information and appeal, personalization, exclamation mark (logos), encouragement of an emphatic spirit (pathos), and reference to elite members (ethos). The most expressive issue in press releases (N=17) is “public support/promotion of actions benefiting the cause of rare diseases” and the most frequent sources are EURORDIS’ direction. Rhetorical analysis reveals the focus on the target public – journalists –, confirmed by the use of a predominantly informative language style.

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Mining Facebook Data of People with Rare Diseases

Cited by 5 publications

References 17 publications

Mining Facebook Data of People with Rare Diseases: A Content-Based and Temporal Analysis

Mining Facebook Data of People with Rare Diseases: A Content-Based and Temporal Analysis

Looking for Emergent Systems in Computer-Based Medical Systems: A Review from the Last Decade

E-public Relations in Health Organizations: How EURORDIS-Rare Diseases Europe Uses the Website and Facebook to Communicate with Key Publics

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