{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,4]],"date-time":"2025-10-04T14:28:32Z","timestamp":1759588112625},"publisher-location":"Cham","reference-count":24,"publisher":"Springer International Publishing","isbn-type":[{"type":"print","value":"9783319737058"},{"type":"electronic","value":"9783319737065"}],"license":[{"start":{"date-parts":[[2018,1,1]],"date-time":"2018-01-01T00:00:00Z","timestamp":1514764800000},"content-version":"unspecified","delay-in-days":0,"URL":"http:\/\/creativecommons.org\/licenses\/by\/4.0"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2018]]},"DOI":"10.1007\/978-3-319-73706-5_21","type":"book-chapter","created":{"date-parts":[[2018,1,5]],"date-time":"2018-01-05T15:55:40Z","timestamp":1515167740000},"page":"248-255","update-policy":"http:\/\/dx.doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":11,"title":["Twitter Geolocation Prediction Using Neural Networks"],"prefix":"10.1007","author":[{"given":"Philippe","family":"Thomas","sequence":"first","affiliation":[]},{"given":"Leonhard","family":"Hennig","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2018,1,6]]},"reference":[{"key":"21_CR1","unstructured":"Chi, L., Lim, K.H., Alam, N., Butler, C.J.: Geolocation prediction in Twitter using location indicative words and textual features. In: Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT), Osaka, Japan, pp. 227\u2013234, December 2016. http:\/\/aclweb.org\/anthology\/W16-3930"},{"key":"21_CR2","unstructured":"Davis, M., Whistler, K., D\u00fcrst, M.: Unicode Normalization Forms. Technical report, Unicode Consortium (2001)"},{"key":"21_CR3","unstructured":"Guo, C., Berkhahn, F.: Entity embeddings of categorical variables. CoRR, abs\/1604.06737 (2016)"},{"key":"21_CR4","unstructured":"Han, B., Baldwin, T.: Lexical normalisation of short text messages: makn sens a #Twitter. In: Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies, HLT 2011, Stroudsburg, PA, USA, vol. 1, pp. 368\u2013378 (2011). http:\/\/dl.acm.org\/citation.cfm?id=2002472.2002520 . ISBN 978-1-932432-87-9"},{"key":"21_CR5","unstructured":"Han, B., Cook, P., Baldwin, T.: Geolocation prediction in social media data by finding location indicative words. In: COLING 2012, 24th International Conference on Computational Linguistics, Proceedings of the Conference: Technical Papers, Mumbai, India, pp. 1045\u20131062, 8\u201315 December 2012. http:\/\/aclweb.org\/anthology\/C\/C12\/C12-1064.pdf"},{"issue":"1","key":"21_CR6","first-page":"451","volume":"49","author":"B Han","year":"2014","unstructured":"Han, B., Cook, P., Baldwin, T.: Text-based Twitter user geolocation prediction. J. Artif. Int. Res. 49(1), 451\u2013500 (2014). http:\/\/dl.acm.org\/citation.cfm?id=2655713.2655726 . ISSN 1076-9757","journal-title":"J. Artif. Int. Res."},{"key":"21_CR7","unstructured":"Han, B., Rahimi, A., Derczynski, L., Baldwin, T.: Twitter geolocation prediction shared task of the 2016 workshop on noisy user-generated text. In: Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT), Osaka, Japan, pp. 213\u2013217, December 2016. http:\/\/aclweb.org\/anthology\/W16-3928"},{"issue":"8","key":"21_CR8","doi-asserted-by":"publisher","first-page":"1735","DOI":"10.1162\/neco.1997.9.8.1735","volume":"9","author":"S Hochreiter","year":"1997","unstructured":"Hochreiter, S., Schmidhuber, J.: Long short-term memory. Neural Comput. 9(8), 1735\u20131780 (1997). https:\/\/doi.org\/10.1162\/neco.1997.9.8.1735 . ISSN 0899\u20137667","journal-title":"Neural Comput."},{"key":"21_CR9","unstructured":"Ioffe, S., Szegedy, C.: Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift. CoRR, abs\/1502.03167 (2015). http:\/\/arxiv.org\/abs\/1502.03167"},{"key":"21_CR10","unstructured":"Jayasinghe, G., Jin, B., Mchugh, J., Robinson, B., Wan, S.: CSIRO Data61 at the WNUT Geo Shared Task. In: Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT), Osaka, Japan, pp. 218\u2013226, December 2016. http:\/\/aclweb.org\/anthology\/W16-3929"},{"key":"21_CR11","unstructured":"Joulin, A., Grave, E., Bojanowski, P., Mikolov, T.: Bag of Tricks for Efficient Text Classification. CoRR, abs\/1607.01759 (2016). http:\/\/arxiv.org\/abs\/1607.01759"},{"key":"21_CR12","doi-asserted-by":"crossref","unstructured":"Jurgens, D., Finethy, T., McCorriston, J., Xu, Y.T., Ruths, D.: Geolocation prediction in Twitter using social networks: a critical analysis and review of current practice. In: ICWSM, pp. 188\u2013197 (2015)","DOI":"10.1609\/icwsm.v9i1.14627"},{"key":"21_CR13","unstructured":"Kingma, D.P., Ba, J.: Adam: A Method for Stochastic Optimization. CoRR, abs\/1412.6980 (2014). http:\/\/arxiv.org\/abs\/1412.6980"},{"key":"21_CR14","doi-asserted-by":"crossref","unstructured":"Liu, J., Inkpen, D.: Estimating user location in social media with stacked denoising auto-encoders. In: Proceedings of the 1st Workshop on Vector Space Modeling for Natural Language Processing, Denver, Colorado, pp. 201\u2013210, June 2015. http:\/\/www.aclweb.org\/anthology\/W15-1527","DOI":"10.3115\/v1\/W15-1527"},{"key":"21_CR15","unstructured":"Mikolov, T., Sutskever, I., Chen, K., Corrado, G., Dean, J.: Distributed Representations of Words and Phrases and their Compositionality. CoRR, abs\/1310.4546 (2013). http:\/\/arxiv.org\/abs\/1310.4546"},{"key":"21_CR16","unstructured":"Miura, Y., Taniguchi, M., Taniguchi, T., Ohkuma, T.: A simple scalable neural networks based model for geolocation prediction in Twitter. In: Proceedings of the 2nd Workshop on Noisy User-generated Text (WNUT), Osaka, Japan, pp. 235\u2013239, December 2016. http:\/\/aclweb.org\/anthology\/W16-3931"},{"key":"21_CR17","doi-asserted-by":"crossref","unstructured":"Paul, M.J., Dredze, M., Broniatowski, D.: Twitter improves influenza forecasting. PLOS Currents Outbreaks 6 (2014)","DOI":"10.1371\/currents.outbreaks.90b9ed0f59bae4ccaa683a39865d9117"},{"key":"21_CR18","unstructured":"Power, R., Robinson, B., Ratcliffe, D.: Finding fires with Twitter. In: Australasian Language Technology Association Workshop, vol. 80 (2013)"},{"key":"21_CR19","doi-asserted-by":"crossref","unstructured":"Rahimi, A., Cohn, T., Baldwin, T.: Pigeo: a python geotagging tool. In: Proceedings of ACL-2016 System Demonstrations, Berlin, Germany, pp. 127\u2013132, August 2016. http:\/\/anthology.aclweb.org\/P16-4022","DOI":"10.18653\/v1\/P16-4022"},{"key":"21_CR20","unstructured":"Simonyan, K., Zisserman, A.: Very Deep Convolutional Networks for Large-Scale Image Recognition. CoRR, abs\/1409.1556 (2014). http:\/\/arxiv.org\/abs\/1409.1556"},{"key":"21_CR21","doi-asserted-by":"publisher","unstructured":"Sloan, L., Morgan, J., Housley, W., Williams, M., Edwards, A., Burnap, P., Rana, O.: Knowing the tweeters: deriving sociologically relevant demographics from Twitter. Sociol. Res. Online, 18 (3) (2013). https:\/\/doi.org\/10.5153\/sro.3001 . ISSN 1360\u20137804","DOI":"10.5153\/sro.3001"},{"issue":"1","key":"21_CR22","first-page":"1929","volume":"15","author":"N Srivastava","year":"2014","unstructured":"Srivastava, N., Hinton, G., Krizhevsky, A., Sutskever, I., Salakhutdinov, R.: Dropout: a simple way to prevent neural networks from overfitting. J. Mach. Learn. Res. 15(1), 1929\u20131958 (2014). http:\/\/dl.acm.org\/citation.cfm?id=2627435.2670313 . ISSN 1532\u20134435","journal-title":"J. Mach. Learn. Res."},{"key":"21_CR23","doi-asserted-by":"publisher","unstructured":"Vincent, P., Larochelle, H., Bengio, Y., Manzagol, P.-A.: Extracting and composing robust features with denoising autoencoders. In: Proceedings of the 25th International Conference on Machine Learning, ICML 2008, New York, NY, USA, pp. 1096\u20131103. ACM (2008). https:\/\/doi.org\/10.1145\/1390156.1390294 . ISBN 978-1-60558-205-4","DOI":"10.1145\/1390156.1390294"},{"key":"21_CR24","doi-asserted-by":"publisher","unstructured":"Ye, M., Yin, P., Lee, W.-C.: Location recommendation for location-based social networks. In: Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems, GIS 2010, pp. 458\u2013461, New York, NY, USA. ACM (2010). https:\/\/doi.org\/10.1145\/1869790.1869861 . ISBN 978-1-4503-0428-3","DOI":"10.1145\/1869790.1869861"}],"container-title":["Lecture Notes in Computer Science","Language Technologies for the Challenges of the Digital Age"],"original-title":[],"link":[{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/978-3-319-73706-5_21","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2023,8,30]],"date-time":"2023-08-30T12:03:35Z","timestamp":1693397015000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/978-3-319-73706-5_21"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018]]},"ISBN":["9783319737058","9783319737065"],"references-count":24,"URL":"https:\/\/doi.org\/10.1007\/978-3-319-73706-5_21","relation":{},"ISSN":["0302-9743","1611-3349"],"issn-type":[{"type":"print","value":"0302-9743"},{"type":"electronic","value":"1611-3349"}],"subject":[],"published":{"date-parts":[[2018]]}}}