In order to help other group recommender application developers and designers I here provide an anonymized dataset.
In case you manage to obtain good results with my dataset and publish you should cite my work and the origin of the dataset.
DataSet of Group Recommender Systems Enhanced by Social Elements by Lara Quijano is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 3.0 Unported License.
Based on a work at Group Recommender Systems Enhanced by Social Elements related papers.
To gather the data here presented I used my Facebook application HappyMovie. This dataset is a small sample of 58 users and 15 groups of different sizes.
During the experiment I employed the following instruments:
- TKI metaphor: It is a personality test based on the TKI test [Thomas and Kilmann 1974]. This test is used to obtain a personality profile about the way a person deals with conflict.
- Movie listing: A list of 15 recent movies (of year 2009), which represents a movie listing from a cinema. This movie listing was chosen heterogeneously from movies from the MovieLens data set [Bobadilla et al. 2009].
- Movies to rate: A list of 50 movies selected from the MovieLens data set.
The experiment was carried out as follows:
- Every user completed two different questionnaires (personality and preferences test). The answers to these questionnaires were analyzed to define each participants’ user profile, which contains information about their personality and their individual movie preferences.
- The trust between users was automatically computed by extracting social information from users’ Facebook profiles.
- I managed to form groups of users. Afterwards, I asked each group to choose which 3 movies from the Movie Listing they would actually watch together.