2024-12-24 11:00: Our storage is full. Uploading files will be possible again from December 28, 2024.

Data and code underlying the BSc thesis: Towards Effective Smoking Cessation: Understanding the Needs of Daily Smokers from eHealth Chatbot Interactions

doi:10.4121/257decd4-5980-4731-a368-67abfca7c308.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/257decd4-5980-4731-a368-67abfca7c308
Datacite citation style:
Iftimescu, Vlad (2024): Data and code underlying the BSc thesis: Towards Effective Smoking Cessation: Understanding the Needs of Daily Smokers from eHealth Chatbot Interactions. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/257decd4-5980-4731-a368-67abfca7c308.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset

This dataset serves for providing readers with information to understand and reproduce the analysis described in the Bachelor's thesis paper: "Towards Effective Smoking Cessation: Understanding the Needs of Daily Smokers from eHealth Chatbot Interactions" by Vlad-Gabriel Iftimescu. The objective of this research is to provide an analysis of users' needs based on a dataset of daily smokers' interactions with a chatbot designed to help them quit. The identified needs of the users have been correlated with some of their personal characteristics. The responses of the users to their interactions with the chatbot, together with their ages, genders and education levels were gathered as part of the Perfect Fit study (project number 628.011.211). This dataset contains anonymized Excel files with the Perfect Fit data, Python scripts which were used to process said data, as well as images depicting the results from various steps of the analysis.

history
  • 2024-01-29 first online, published, posted
publisher
4TU.ResearchData
format
.zip archive containing Python scripts, .xlsx files, .png images, together with a .pdf file and a README.md.
funding
  • Part of Perfect Fit, funded by NWO, project number 628.011.211
organizations
TU Delft, Faculty Electrical Engineering, Mathematics and Computer Science

DATA

files (1)