Data-Gouv-ML/catalogue-des-donnees-Sql-Lite huggingface dataset:
Credibility Corpus with several datasets (Twitter, Web database) in French and English

Description of the corpora

The set of these datasets are made to analyze ifnormation credibility in general 
(rumor and disinformation for English and French documents), 
and occuring on the social web. 
Target databases about rumor, hoax and disinformation helped to 
collect obviously misinformation. Some topic (with keywords) helps us to made corpora from the micrroblogging
platform Twitter, great provider of rumors and disinformation.

1 corpus describes Texts from the web database about rumors and disinformation.
4 corpora from Social Media Twitter about specific rumors (2 in English, 2 in French).
4 corpora from Social Media Twitter randomly built (2 in English, 2 in French).
4 corpora from Social Media Twitter about specific rumors (2 in English, 2 in French).

Size of different corpora :

Social Web Rumorous corpus:			1,612

French Hollande Rumorous corpus (Twitter):	371
French Lemon Rumorous corpus (Twitter):		270
English Pin Rumorous corpus (Twitter):		679
English Swine Rumorous corpus (Twitter):	1024

French 1st Random corpus  (Twitter):		1000
French 2st Random corpus  (Twitter):		1000
English 3st Random corpus  (Twitter):		1000
English 4st Random corpus  (Twitter):		1000

French Rihanna Event corpus (Twitter):		543
English Rihanna Event corpus (Twitter):		1000
French Euro2016 Event corpus (Twitter):		1000
English Euro2016 Event corpus (Twitter):	1000

A matrix links tweets with most 50 frequent words

Text data :

_id :		message id
body text : 	string text data

Matrix data :

52 columns (first column is id, second column is rumor indicator 1 or -1, other columns are words value is 1 contain or 0 does not contain)
11,102 lines (each line is a message)

Hidalgo corpus: lines range   1:75
Lemon corpus :  lines range  76:467
Pin rumor :     lines range 468:656
swine :         lines range 657:1311

random messages : lines range 1312:11103


Sample contains :
French Pin Rumorous corpus (Twitter):		679
Matrix data :

52 columns (first column is id, second column is rumor indicator 1 or -1, other columns are words value is 1 contain or 0 does not contain)
189 lines (each line is a message)


Fréquence de mise à jour : unknown
Début de la couverture temporelle : 2006-01-01
Fin de la couverture temporelle : 2015-07-01
Open Bilbio corpus for content analysis

Description of the corpus

The corpus describes fulltexts publication in sciences (mathemtaics, computing, statistics) in LATEX or TXT format.
They are published in open access.

Purprose to use this corpus is twice :

- information extraction (for instance: extract all collocations around a target word, or extract methods names)
- comparison of abstract and body text


size of publication corpus  : 650,000
size of publication sample :       20 


data :

body string text data

Fréquence de mise à jour : semiannual
Début de la couverture temporelle : 1994-01-01
Fin de la couverture temporelle : 2014-07-01
archive de youtube sur le lancement d'alerte

Description of the corpus

The corpus describes videos about whistleblowing on the Youtube social media. 
Goal of the corpus is the detect automatically new videos (persons or organizations) emitting whistleblowing.
The corpus aims at finding patterns for that purpose.



size of video corpus  : 347,544
size of video sample :       22 (one for each topic class)

metadata :

_id :	video id
title : video title
channelid : channel id
channeltitle : channel title
datepub : publication date of the video 
description : description field of the video
tags : list of keywords for a video
kind : a type , for instance youtube#video
defaultaudiolang : default language of a video 
viewcount : number of views for a video
likecount : number of users who likes a video
dislikecount : number of users who do not like a video
commentscount : number of comments
comments : a list of comments :
    author : author of a comment
    like : number of users who like the comment
    message : content of a comment
transcription : video transcription in free text

Fréquence de mise à jour : semiannual
Début de la couverture temporelle : 2007-01-01
Fin de la couverture temporelle : 2016-11-30