We have relevant datasets, repositories, frameworks and tools of relevance for research and technology transfer initiatives related to knowledge extraction. This section provides an overview on a selection of them and links to download or contact details.

The MdM Strategic Research Program has its own community in Zenodo for material available in this repository  as well as at the UPF e-repository  . Below a non-exhaustive list of datasets representative of the research in the Department.

As part of the promotion of the availability of resources, the creation of specific communities in Zenodo has also been promoted, at level of research communities (for instance, MIR and Educational Data Analytics) or MSc programs (for instance, the Master in Sound and Music Computing)

 

 

Back [TEXT] Dataset of discussion threads from Meneame

[TEXT] Dataset of discussion threads from Meneame

Crawling process

We built a crawling process that collects all the stories in the front page of Meneame from 2011 to 2015 (both years included). We then performed a second crawling process to collect every comment from the discussion thread of each story. From both crawling processes, we obtained 72,005 stories and 5,385,324 comments.

It is important to highlight two issues taken into account when the crawler was designed. First, the machine-readable robots.txt file on Meneame does not disallow this process. Second, the footnote of Meneame indicates the licenses of the code, graphics and content of the website. The license for content is Attribution 3.0 Spain (CC BY 3.0 ES) which allows us to release this dataset.

More information http://doi.org/10.5281/zenodo.2536218

Dataset from our ICWSM 2017 paper. When using this resource, please use the following citation:

Aragón P., Gómez V., Kaltenbrunner A. (2017) To Thread or Not to Thread: The Impact of Conversation Threading on Online Discussion, ICWSM-17- 11th International AAAI Conference on Web and Social Media, Montreal, Canada.

More info about this dataset can also be found at:

Aragón P., Gómez V., Kaltenbrunner A., (2017) Detecting Platform Effects in Online Discussions, Policy & Internet, 9, 2017.