B. , T. Adler, K. Chatterjee, M. Luca-de-alfaro, I. Faella et al., Assigning trust to Wikipedia content, WikiSym, 2008.
DOI : 10.1145/1822258.1822293

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

R. Agrawal and . Luca-de-alfaro, Predicting the quality of user contributions via LSTMs, Proceedings of the 12th International Symposium on Open Collaboration, OpenSym '16, 2016.
DOI : 10.1145/1296951.1296968

M. Anderka, B. Stein, and N. Lipka, Predicting quality flaws in user-generated content, Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval, SIGIR '12, pp.981-990, 2012.
DOI : 10.1145/2348283.2348413

Y. Aphinyanaphongs, L. D. Fu, Z. Li, E. R. Peskin, E. Efstathiadis et al., A comprehensive empirical comparison of modern supervised classification and feature selection methods for text categorization, Journal of the Association for Information Science and Technology, vol.9, issue.3, pp.10-1964, 2014.
DOI : 10.2307/2531595

J. Bergstra and Y. Bengio, Random Search for Hyper-Parameter Optimization, Journal of Machine Learning Research, vol.13, pp.281-305, 2012.

A. Grace-gimon-betancourt, C. Segnine, A. Trabuco, N. Rezgui, and . Jullien, Mining team characteristics to predict Wikipedia article quality, OpenSym, 2016.

J. E. Blumenstock, Size matters, Proceeding of the 17th international conference on World Wide Web , WWW '08, 2008.
DOI : 10.1145/1367497.1367673

R. Adam and . Brown, Wikipedia as a data source for political scientists: Accuracy and completeness of coverage, PS: Political Science & Politics, 2011.

N. Buduma and N. Locascio, Fundamentals of Deep Learning: Designing Next-generation Machine Intelligence Algorithms, 2017.

G. Chandrashekar and F. Sahin, A survey on feature selection methods, Computers & Electrical Engineering, vol.40, issue.1, pp.16-28, 2014.
DOI : 10.1016/j.compeleceng.2013.11.024

J. Chung, Ç. Gülçehre, K. Cho, and Y. Bengio, Empirical Evaluation of Gated Recurrent Neural Networks on Sequence Modeling, p.3555, 2014.

M. A. Daniel-hasan-dalip, M. Gonçalves, P. Cristo, and . Calado, Automatic quality assessment of content created collaboratively by web communities, Proceedings of the 2009 joint international conference on Digital libraries, JCDL '09, 2009.
DOI : 10.1145/1555400.1555449

Q. Dang and C. Ignat, Quality assessment of wikipedia articles: a deep learning approach, SIGWEB Newsletter, 2016.
URL : https://hal.archives-ouvertes.fr/hal-01393227

Q. Dang and C. Ignat, Quality Assessment of Wikipedia Articles without Feature Engineering, Proceedings of the 16th ACM/IEEE-CS on Joint Conference on Digital Libraries, JCDL '16, 2016.
DOI : 10.1145/2462932.2462948

URL : https://hal.archives-ouvertes.fr/hal-01351226

Q. Vinh, D. , and C. Ignat, Measuring Quality of Collaboratively Edited Documents: The Case of Wikipedia, CIC. IEEE, 2016.

L. Baptiste-de, Y. Robertie, O. Pitarch, and . Teste, Measuring Article Quality in Wikipedia using the Collaboration Network, ASONAM, 2015.

M. Eliasziw and A. Donner, Application of the McNemar test to non-independent matched pair data, Statistics in Medicine, vol.33, issue.12, pp.12-1981, 1991.
DOI : 10.1002/sim.4780101211

Y. Gal and Z. Ghahramani, A Theoretically Grounded Application of Dropout in Recurrent Neural Networks, NIPS, 2016.

I. Goodfellow, Y. Bengio, and A. Courville, Deep Learning, 2016.

E. Grave, A. Joulin, M. Cissé, D. Grangier, and H. Jégou, Efficient softmax approximation for GPUs, p.4309, 2016.

A. Graves, Supervised Sequence Labelling with Recurrent Neural Networks, Studies in Computational Intelligence, vol.385, 2012.
DOI : 10.1007/978-3-642-24797-2

A. Graves, Generating Sequences With Recurrent Neural Networks, p.850, 2013.

A. Graves, Adaptive Computation Time for Recurrent Neural Networks CoRR abs/1603, p.8983, 2016.

A. Halfaker, A. Kittur, and J. Riedl, Don't bite the newbies, Proceedings of the 7th International Symposium on Wikis and Open Collaboration, WikiSym '11, 2011.
DOI : 10.1145/2038558.2038585

A. Halfaker and D. Taraborelli, Artificial intelligence service gives Wikipedians 'X-ray specs' to see through bad edits. (2015). https://blog.wikimedia. org, 2015.

A. Halfaker and M. Warncke-wang, Wikipedia article quality classification (retrieved 12, 2017.

J. David, R. J. Hand, and . Till, A Simple Generalisation of the Area Under the ROC Curve for Multiple Class Classification Problems, Machine Learning, vol.45, issue.2, pp.171-186, 2001.

S. Hochreiter and J. Schmidhuber, Long Short-Term Memory, Neural Computation, vol.4, issue.8, pp.1735-1780, 1997.
DOI : 10.1016/0893-6080(88)90007-X

M. Hu and E. Lim, Aixin Sun, Hady Wirawan Lauw, and Ba-Quy Vuong Measuring article quality in wikipedia: models and evaluation, CIKM, 2007.

J. Huang and C. X. Ling, Using AUC and accuracy in evaluating learning algorithms, IEEE Transactions on Knowledge and Data Engineering, vol.17, issue.3, pp.299-310, 2005.
DOI : 10.1109/TKDE.2005.50

N. Japkowicz and M. Shah, Evaluating learning algorithms: a classification perspective, 2011.
DOI : 10.1017/CBO9780511921803

S. Javanmardi and C. Lopes, Statistical measure of quality in Wikipedia, Proceedings of the First Workshop on Social Media Analytics, SOMA '10, 2010.
DOI : 10.1145/1964858.1964876

S. Jones, The social life of health information. Pew research center, 2009.

R. Józefowicz, W. Zaremba, and I. Sutskever, An Empirical Exploration of Recurrent Network Architectures, ICML, 2015.

A. Karpathy, J. Johnson, and F. Li, Visualizing and Understanding Recurrent Networks, p.2078, 2015.

P. Diederik, J. Kingma, and . Ba, Adam: A Method for Stochastic Optimization, ICLR, 2015.

A. Kittur and R. E. Kraut, Harnessing the wisdom of crowds in wikipedia, Proceedings of the ACM 2008 conference on Computer supported cooperative work, CSCW '08, pp.37-46, 2008.
DOI : 10.1145/1460563.1460572

G. De, L. Calzada, and A. Dekhtyar, On measuring the quality of Wikipedia articles, WICOW, 2010.

V. Quoc, T. Le, and . Mikolov, Distributed Representations of Sentences and Documents, ICML, 2014.

X. Li, J. Tang, T. Wang, Z. Luo, and M. De-rijke, Automatically Assessing Wikipedia Article Quality by Exploiting Article???Editor Networks, ECIR, 2015.
DOI : 10.1007/978-3-319-16354-3_64

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

N. Lipka and B. Stein, Identifying featured articles in wikipedia, Proceedings of the 19th international conference on World wide web, WWW '10, 2010.
DOI : 10.1145/1772690.1772847

J. Liu and S. Ram, Who does what, ACM Transactions on Management Information Systems, vol.2, issue.2, 2011.
DOI : 10.1145/1985347.1985352

J. Mao, J. Xu, K. Jing, and A. L. Yuille, Training and Evaluating Multimodal Word Embeddings with Large-scale Web Annotated Images, NIPS, 2016.

D. Molchanov, A. Ashukha, and D. Vetrov, Variational Dropout Sparsifies Deep Neural Networks, p.5369, 2017.

K. Nemoto, P. A. Gloor, and R. Laubacher, Social capital increases efficiency of collaboration among Wikipedia editors, Proceedings of the 22nd ACM conference on Hypertext and hypermedia, HT '11, 2011.
DOI : 10.1145/1995966.1995997

URL : http://citeseerx.ist.psu.edu/viewdoc/summary?doi=

A. Ng, Machine Learning and AI via Brain simulations, 2013.

M. Túlio-ribeiro, S. Singh, and C. Guestrin, Why Should I Trust You?": Explaining the Predictions of Any Classifier, KDD, 2016.

A. Rosenblueth and N. Wiener, The Role of Models in Science, Philosophy of Science, vol.12, issue.4, 1945.
DOI : 10.1086/286874

E. David, G. E. Rumelhart, R. J. Hinton, and . Williams, Learning representations by back-propagating errors, Nature, vol.323, issue.6088, pp.533-536, 0910.

K. Stein and C. Hess, Does it matter who contributes, Proceedings of the 18th conference on Hypertext and hypermedia , HT '07, 2007.
DOI : 10.1145/1286240.1286290

Y. Suzuki, Quality Assessment of Wikipedia Articles Using h-index, Journal of Information Processing, vol.23, issue.1, pp.22-30, 2015.
DOI : 10.2197/ipsjjip.23.22

M. Warncke-wang, V. R. Ayukaev, B. Hecht, and L. G. Terveen, The Success and Failure of Quality Improvement Projects in Peer Production Communities, Proceedings of the 18th ACM Conference on Computer Supported Cooperative Work & Social Computing, CSCW '15, 2015.
DOI : 10.1002/asi.20813

M. Warncke-wang, D. Cosley, and J. Riedl, Tell me more, Proceedings of the 9th International Symposium on Open Collaboration, WikiSym '13, 2013.
DOI : 10.1145/2491055.2491063

J. Watt, R. Borhani, and A. Katsaggelos, Machine Learning Refined: Foundations, Algorithms, and Applications, 2016.
DOI : 10.1017/CBO9781316402276

K. Weiss, M. Taghi, D. Khoshgoftaar, and . Wang, A survey of transfer learning, Journal of Big Data, vol.28, issue.3, pp.1-40, 2016.
DOI : 10.1145/1557019.1557130

. Wikimedia, Objective Revision Evaluation Service (retrieved 24, 2017.

M. Dennis, B. A. Wilkinson, and . Huberman, Cooperation and quality in Wikipedia, WikiSym, 2007.

G. Wu, M. Harrigan, and P. Cunningham, Classifying Wikipedia articles using network motif counts and ratios, Proceedings of the Eighth Annual International Symposium on Wikis and Open Collaboration, WikiSym '12, 2012.
DOI : 10.1145/2462932.2462948

Y. Xu and T. Luo, Measuring article quality in Wikipedia: Lexical clue model, SWS, 2011.

W. Zaremba, I. Sutskever, and O. Vinyals, Recurrent Neural Network Regularization, p.2329, 2015.

Y. Zheng, G. Li, Y. Li, C. Shan, and R. Cheng, Truth inference in crowdsourcing, Proceedings of the VLDB Endowment, vol.10, issue.5, pp.541-552, 2017.
DOI : 10.14778/3055540.3055547