E. Fleury, ENS de Lyon / Inria https://team.inria.fr/dante/

CLARIN-PLUS workshop — Creation and Use of Social Media Resources, May 2017

https://sosweet.inria.fr

Outline

n Objectives of SoSweet

n Data collections

n Tools

n Future Challenges

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Objectives #1n Provide a detailed understanding of the dynamic links between: q individuals, q social structure, q and language variation and change

n through the study of: q synchronic variation q diachronic evolution q of the variety of French language observed on

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Objectives #2n Develop

q interdisciplinary, q computational and data driven approaches

n to handle the enormous amount of collected digital data specific to social media

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Twitter as a labto study how social structure shapes linguistic variability and change

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Language on Twitter shows n High variability n High innovation rates

Twitter provides large amount of n Linguistics data n Social data

Not forgetting bias n Technological bias n Communicative bias

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Corpuslinguis,cs Sociolinguis,cs

NaturalLanguageProcessing Networkscience

Linguis'cDatatweets

SocialDataFollowersnetwork

SynchronyLinguis,cvaria,on/Socialstructure

DiachronyLanguagechange/Socialstructure

Outline

n Objectives of SoSweet

n Data collections

n Tools

n Future Challenges

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Data collection: tweets

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I leave in GMT or GMT+1

June 2014 Dec 2019

I tweet in French

Target 500 million tweets n 200 millions n annotated with parts of

speech n Gnip/Datasift/JSON

Processed / TAG (CC Tagset)

Now

Data collection: networks

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I have followers

June 2014 Dec 2019

and followees target 10 million users

n 2 millions n authored tweets n followees n followers

Now

Data collection: socio-economic data

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I answer fun quiz and some demographic questions

http://sosweet.ish-lyon.cnrs.fr

Outline

n Objectives of SoSweet

n Data collections

n Tools

n Future Challenges

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ALMAnaCH Linguistic workbenchn MELT:Part Of Speech tagger

q Coupling annotated corpus / morphosyntactic lexicon

n FRMG — French Meta Grammar q Wide coverage abstract grammatical

description for French n Word Embeddings with Glove/FRMG

q Global Vectors for Word Representation q syntax link / not only co-ocurence

n https://gforge.inria.fr/projects/lingwb/

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Word2Graph embedding

n Use Glove or word2vect q embedding of the vocabulary to a « space »

n Build a k-closest proximity graph on q Two word close in the space are link q Non symmetric relation

n Run community detection on the proximity graph

q https://gitlab.inria.fr

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Outline

n Objectives of SoSweet

n Data collections

n Tools

n Future Challenges

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Open SoSweet to the communityn Ethical issues

q Operational Legal and Ethical Risk Assessment Committee (COERLE)

n Licensing issues / Twitter restriction No full tweets distribution Distributing IDs is allowed

n Aggregation n Sampling n On line tools for queries.

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Thanks

ICARMa#hieuQuignardSandraTeston-BonnardClémentThibertNathalieRossy-GensaneDanielValéro

LidilemJean-PierreChevrotAurélieNardyJuliePeuvergne

AlpageMarieCanditoEricdelaClergerieBenoîtCrabbéBenoîtSagotDjaméSeddah

DanteEricFleuryMartonKarsaiHadrienHoursSa:iJouaberJacobLevy-AbitbolTommasoVenturini