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Novel Approach to Cluster Patient-Generated Data Into Actionable Topics: Case Study of a Web-Based Breast Cancer Forum

After scraping the forum data and saving into 80 files representing each forum, the files were imported into the MALLET tool. MALLET generates two tab-delimited text files as a result of algorithm execution.

Josette Jones, Meeta Pradhan, Masoud Hosseini, Anand Kulanthaivel, Mahmood Hosseini

JMIR Med Inform 2018;6(4):e45

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Health System Stakeholders’ Perspective on the Role of Mobile Health and Its Adoption in the Swiss Health System: Qualitative Study

Myriam Lingg, Verena Lütschg

JMIR Mhealth Uhealth 2020;8(5):e17315

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Enhancing Seasonal Influenza Surveillance: Topic Analysis of Widely Used Medicinal Drugs Using Twitter Data

The LDA method was implemented by MALLET (University of Massachusetts Amherst) [58].The number of topics retrieved for tweets about each drug was varied using an optimum topic number test as suggested by a previous method [59].

Ireneus Kagashe, Zhijun Yan, Imran Suheryani

J Med Internet Res 2017;19(9):e315

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What Online Communities Can Tell Us About Electronic Cigarettes and Hookah Use: A Study Using Text Mining and Visualization Techniques

LDA is a technique that models documents as random mixtures over topics, where a topic is characterized as a distribution of words [41].We employed the LDA implementation that is available with the MALLET toolkit [42].

Annie T Chen, Shu-Hong Zhu, Mike Conway

J Med Internet Res 2015;17(9):e220

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Effects of Three Antecedents of Patient Compliance for Users of Peer-to-Peer Online Health Communities: Cross-Sectional Study

Anne-Françoise Audrain-Pontevia, Loick Menvielle, Myriam Ertz

J Med Internet Res 2019;21(11):e14006

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An Educational Network for Surgical Education Supported by Gamification Elements: Protocol for a Randomized Controlled Trial

Natasha Guérard-Poirier, Michèle Beniey, Léamarie Meloche-Dumas, Florence Lebel-Guay, Bojana Misheva, Myriam Abbas, Malek Dhane, Myriam Elraheb, Adam Dubrowski, Erica Patocskai

JMIR Res Protoc 2020;9(12):e21273

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Demystifying the Dark Web Opioid Trade: Content Analysis on Anonymous Market Listings and Forum Posts

Zhengyi Li, Xiangyu Du, Xiaojing Liao, Xiaoqian Jiang, Tiffany Champagne-Langabeer

J Med Internet Res 2021;23(2):e24486

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Variations in Facebook Posting Patterns Across Validated Patient Health Conditions: A Prospective Cohort Study

To distil the language of our sample into a smaller feature space, we used a natural language processing technique; specifically, we used an unsupervised clustering algorithm, latent Dirichlet allocation (LDA) [14] implemented in the MALLET package [15].

Robert J Smith, Patrick Crutchley, H Andrew Schwartz, Lyle Ungar, Frances Shofer, Kevin A Padrez, Raina M Merchant

J Med Internet Res 2017;19(1):e7

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Validation of a Portable Game Controller to Assess Peak Expiratory Flow Against Conventional Spirometry in Children: Cross-sectional Study

Khadidja Chelabi, Fabio Balli, Myriam Bransi, Yannick Gervais, Clement Marthe, Sze Man Tse

JMIR Serious Games 2021;9(1):e25052

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#Healthy Selfies: Exploration of Health Topics on Instagram

We used the Polylingual Topic Model implementation from MALLET [37]. The hyperparameter for the topic distribution prior (ie, “alpha”) was set to 1.0, and we used the default algorithm settings. The number of topics was set to 150.

Sachin Muralidhara, Michael J. Paul

JMIR Public Health Surveill 2018;4(2):e10150

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