This corpus has been collected using the YouTube Data API v3.

Data Set Information:

The table below lists the datasets, the YouTube video ID, the amount of samples in each class and the total number of samples per dataset.

Dataset --- YouTube ID -- # Spam - # Ham - Total
Psy ------- 9bZkp7q19f0 --- 175 --- 175 --- 350
KatyPerry - CevxZvSJLk8 --- 175 --- 175 --- 350
LMFAO ----- KQ6zr6kCPj8 --- 236 --- 202 --- 438
Eminem ---- uelHwf8o7_U --- 245 --- 203 --- 448
Shakira --- pRpeEdMmmQ0 --- 174 --- 196 --- 370

Note: the chronological order of the comments were kept.

Attribute Information:

The collection is composed by one CSV file per dataset, where each line has the following attributes:

COMMENT_ID,AUTHOR,DATE,CONTENT,TAG

We offer one example bellow:

z12oglnpoq3gjh4om04cfdlbgp2uepyytpw0k,Francisco Nora,2013-11-28T19:52:35,please like :D [Web link],1

Relevant Papers:

Alberto, T.C., Lochter J.V., Almeida, T.A. TubeSpam: Comment Spam Filtering on YouTube. Proceedings of the 14th IEEE International Conference on Machine Learning and Applications (ICMLA'15), 1-6, Miami, FL, USA, December, 2015.

T.A. ALMEIDA, T.P. SILVA, I. SANTOS and J.M. GOMEZ HIDALGO. Text Normalization and Semantic Indexing to Enhance Instant Messaging and SMS Spam Filtering. Knowledge-based Systems, Elsevier, 108(2016), 25-32, 2016.

Citation Request:

We would appreciate:

1. If you find this collection useful, make a reference to the paper below and the web page: [Web link].
2. Send us a message either to talmeida < AT > ufscar.br or tuliocasagrande < AT > acm.org in case you make use of the corpus.