{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T05:41:22Z","timestamp":1776404482595,"version":"3.51.2"},"reference-count":47,"publisher":"Springer Science and Business Media LLC","issue":"1","license":[{"start":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T00:00:00Z","timestamp":1776384000000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"},{"start":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T00:00:00Z","timestamp":1776384000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/www.springernature.com\/gp\/researchers\/text-and-data-mining"}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Knowl Inf Syst"],"published-print":{"date-parts":[[2026,12]]},"DOI":"10.1007\/s10115-026-02755-9","type":"journal-article","created":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T04:43:08Z","timestamp":1776400988000},"update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":0,"title":["GAttE: geographic attention model for extraction of users\u2019 current locations from social media texts"],"prefix":"10.1007","volume":"68","author":[{"ORCID":"https:\/\/orcid.org\/0009-0001-2339-6269","authenticated-orcid":false,"given":"Ashish","family":"Kumar","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Manisha","family":"Dubey","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Sangeeta","family":"Sharma","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"297","published-online":{"date-parts":[[2026,4,17]]},"reference":[{"key":"2755_CR1","doi-asserted-by":"crossref","unstructured":"Steedman M (1996) Chapter 8\u2014Natural language processing. In: Boden MA (ed) Artificial intelligence. Handbook of perception and cognition. Academic Press, San Diego, pp 229\u2013266","DOI":"10.1016\/B978-012161964-0\/50010-8"},{"key":"2755_CR2","doi-asserted-by":"publisher","DOI":"10.1016\/j.cosrev.2021.100395","volume":"40","author":"TK Balaji","year":"2021","unstructured":"Balaji TK, Annavarapu CSR, Bablani A (2021) Machine learning algorithms for social media analysis: a survey. Comput Sci Rev 40:100395","journal-title":"Comput Sci Rev"},{"key":"2755_CR3","unstructured":"Song CH, Lawrie D, Finin T, Mayfield J (2020) Improving neural named entity recognition with gazetteers. arXiv preprint arXiv:2003.03072"},{"key":"2755_CR4","doi-asserted-by":"crossref","unstructured":"Imani MB, Chandra S, Ma S, Khan L, Thuraisingham B (2017) Focus location extraction from political news reports with bias correction. In: 2017 IEEE international conference on big data (big data). IEEE, pp 1956\u20131964","DOI":"10.1109\/BigData.2017.8258141"},{"key":"2755_CR5","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijdrr.2022.102783","volume":"70","author":"RI Ogie","year":"2022","unstructured":"Ogie RI, James S, Moore A, Dilworth T, Amirghasemi M, Whittaker J (2022) Social media use in disaster recovery: a systematic literature review. Int J Disaster Risk Reduct 70:102783","journal-title":"Int J Disaster Risk Reduct"},{"key":"2755_CR6","doi-asserted-by":"publisher","DOI":"10.1016\/j.ijdrr.2020.101584","volume":"48","author":"A Saroj","year":"2020","unstructured":"Saroj A, Pal S (2020) Use of social media in crisis management: a survey. Int J Disaster Risk Reduct 48:101584","journal-title":"Int J Disaster Risk Reduct"},{"key":"2755_CR7","doi-asserted-by":"crossref","unstructured":"Banujan K, Kumara BT, Paik I (2018) Twitter and online news analytics for enhancing post-natural disaster management activities. In: 2018 9th international conference on awareness science and technology (iCAST). IEEE, pp 302\u2013307","DOI":"10.1109\/ICAwST.2018.8517195"},{"key":"2755_CR8","doi-asserted-by":"publisher","DOI":"10.1016\/j.scs.2021.103577","volume":"77","author":"M Karimiziarani","year":"2022","unstructured":"Karimiziarani M, Jafarzadegan K, Abbaszadeh P, Shao W, Moradkhani H (2022) Hazard risk awareness and disaster management: extracting the information content of twitter data. Sustain Cities Soc 77:103577","journal-title":"Sustain Cities Soc"},{"key":"2755_CR9","doi-asserted-by":"crossref","unstructured":"Boser BE, Guyon IM, Vapnik VN (1992) A training algorithm for optimal margin classifiers. In: Proceedings of the fifth annual workshop on computational learning theory, pp 144\u2013152","DOI":"10.1145\/130385.130401"},{"key":"2755_CR10","doi-asserted-by":"crossref","unstructured":"Silverman BW, Jones MC (1989) E. fix and jl hodges (1951): An important contribution to nonparametric discriminant analysis and density estimation: Commentary on fix and hodges (1951). Int Stat Rev\/Revue Internationale de Statistique, pp 233\u2013238","DOI":"10.2307\/1403796"},{"issue":"3","key":"2755_CR11","doi-asserted-by":"publisher","first-page":"289","DOI":"10.1080\/13658810701626244","volume":"22","author":"J Leveling","year":"2008","unstructured":"Leveling J, Hartrumpf S (2008) On metonymy recognition for geographic information retrieval. Int J Geogr Inf Sci 22(3):289\u2013299","journal-title":"Int J Geogr Inf Sci"},{"key":"2755_CR12","doi-asserted-by":"crossref","unstructured":"Mahmud J, Nichols J, Drews C (2014) Home location identification of twitter users. arXiv preprint arXiv:1403.2345","DOI":"10.1145\/2528548"},{"key":"2755_CR13","doi-asserted-by":"crossref","unstructured":"Kinsella S, Murdock V, O\u2019Hare N (2011) \u201ci\u2019m eating a sandwich in glasgow\u201d modeling locations with tweets. In: Proceedings of the 3rd international workshop on search and mining user-generated contents, pp 61\u201368 (2011)","DOI":"10.1145\/2065023.2065039"},{"key":"2755_CR14","doi-asserted-by":"crossref","unstructured":"Gonzalez R, Figueroa G, Chen Y-S (2012) Tweolocator: a non-intrusive geographical locator system for twitter. In: Proceedings of the 5th ACM SIGSPATIAL international workshop on location-based social networks, pp 24\u201331","DOI":"10.1145\/2442796.2442804"},{"key":"#cr-split#-2755_CR15.1","unstructured":"Nesi P, Pantaleo G, Tenti M (2014) Ge"},{"key":"#cr-split#-2755_CR15.2","doi-asserted-by":"crossref","unstructured":"(o) lo (cator): Geographic information extraction from unstructured text data and web documents. In: 2014 9th international workshop on semantic and social media adaptation and personalization. IEEE, pp 60-65","DOI":"10.1109\/SMAP.2014.27"},{"issue":"5","key":"2755_CR16","doi-asserted-by":"publisher","first-page":"513","DOI":"10.1016\/0306-4573(88)90021-0","volume":"24","author":"G Salton","year":"1988","unstructured":"Salton G, Buckley C (1988) Term-weighting approaches in automatic text retrieval. Inf Process Manag 24(5):513\u2013523","journal-title":"Inf Process Manag"},{"issue":"1","key":"2755_CR17","doi-asserted-by":"publisher","first-page":"6","DOI":"10.1145\/3404820.3404823","volume":"12","author":"U Qazi","year":"2020","unstructured":"Qazi U, Imran M, Ofli F (2020) Geocov19: a dataset of hundreds of millions of multilingual covid-19 tweets with location information. SIGSPATIAL Spec 12(1):6\u201315","journal-title":"SIGSPATIAL Spec"},{"issue":"1","key":"2755_CR18","doi-asserted-by":"publisher","first-page":"0244918","DOI":"10.1371\/journal.pone.0244918","volume":"16","author":"E Acheson","year":"2021","unstructured":"Acheson E, Purves RS (2021) Extracting and modeling geographic information from scientific articles. PLoS ONE 16(1):0244918","journal-title":"PLoS ONE"},{"key":"2755_CR19","doi-asserted-by":"publisher","DOI":"10.1016\/j.compenvurbsys.2021.101629","volume":"88","author":"N Chen","year":"2021","unstructured":"Chen N, Zhang Y, Du W, Li Y, Chen M, Zheng X (2021) Ke-cnn: a new social sensing method for extracting geographical attributes from text semantic features and its application in wuhan, china. Comput Environ Urban Syst 88:101629","journal-title":"Comput Environ Urban Syst"},{"issue":"3","key":"2755_CR20","doi-asserted-by":"publisher","first-page":"547","DOI":"10.1080\/13658816.2021.1987441","volume":"36","author":"K Stock","year":"2022","unstructured":"Stock K, Jones CB, Russell S, Radke M, Das P, Aflaki N (2022) Detecting geospatial location descriptions in natural language text. Int J Geogr Inf Sci 36(3):547\u2013584","journal-title":"Int J Geogr Inf Sci"},{"issue":"1","key":"2755_CR21","doi-asserted-by":"publisher","DOI":"10.1016\/j.ipm.2021.102735","volume":"59","author":"K Lai","year":"2022","unstructured":"Lai K, Porter JR, Amodeo M, Miller D, Marston M, Armal S (2022) A natural language processing approach to understanding context in the extraction and geocoding of historical floods, storms, and adaptation measures. Inf Process Manag 59(1):102735","journal-title":"Inf Process Manag"},{"issue":"4","key":"2755_CR22","doi-asserted-by":"publisher","first-page":"747","DOI":"10.1080\/13658816.2022.2133125","volume":"37","author":"C Berragan","year":"2023","unstructured":"Berragan C, Singleton A, Calafiore A, Morley J (2023) Transformer based named entity recognition for place name extraction from unstructured text. Int J Geogr Inf Sci 37(4):747\u2013766","journal-title":"Int J Geogr Inf Sci"},{"key":"2755_CR23","doi-asserted-by":"crossref","unstructured":"Chandra S, Khan L, Muhaya FB (2011) Estimating twitter user location using social interactions\u2014a content based approach. In: 2011 IEEE third international conference on privacy, security, risk and trust and 2011 IEEE third international conference on social computing. IEEE, pp 838\u2013843","DOI":"10.1109\/PASSAT\/SocialCom.2011.120"},{"key":"2755_CR24","doi-asserted-by":"publisher","first-page":"50","DOI":"10.1016\/j.dss.2019.03.006","volume":"120","author":"P Zola","year":"2019","unstructured":"Zola P, Cortez P, Carpita M (2019) Twitter user geolocation using web country noun searches. Decis Support Syst 120:50\u201359","journal-title":"Decis Support Syst"},{"key":"2755_CR25","doi-asserted-by":"crossref","unstructured":"Li W, Serdyukov P, Vries AP, Eickhoff C, Larson M (2011) The where in the tweet. In: Proceedings of the 20th ACM international conference on information and knowledge management, pp 2473\u20132476","DOI":"10.1145\/2063576.2063995"},{"issue":"6","key":"2755_CR26","doi-asserted-by":"publisher","first-page":"753","DOI":"10.1111\/j.1467-9671.2011.01294.x","volume":"15","author":"J Gelernter","year":"2011","unstructured":"Gelernter J, Mushegian N (2011) Geo-parsing messages from microtext. Trans GIS 15(6):753\u2013773","journal-title":"Trans GIS"},{"key":"2755_CR27","doi-asserted-by":"crossref","unstructured":"Wanichayapong N, Pruthipunyaskul W, Pattara-Atikom W, Chaovalit P (2011) Social-based traffic information extraction and classification. In: 2011 11th international conference on ITS telecommunications. IEEE, pp 107\u2013112","DOI":"10.1109\/ITST.2011.6060036"},{"key":"2755_CR28","doi-asserted-by":"crossref","unstructured":"Lee K, Ganti R, Srivatsa M, Liu L (2014) When twitter meets foursquare: tweet location prediction using foursquare. In: 11th international conference on mobile and ubiquitous systems: computing, networking and services","DOI":"10.4108\/icst.mobiquitous.2014.258092"},{"issue":"5","key":"2755_CR29","doi-asserted-by":"publisher","first-page":"56","DOI":"10.3390\/ijgi5050056","volume":"5","author":"F Laylavi","year":"2016","unstructured":"Laylavi F, Rajabifard A, Kalantari M (2016) A multi-element approach to location inference of twitter: a case for emergency response. ISPRS Int J Geo Inf 5(5):56","journal-title":"ISPRS Int J Geo Inf"},{"key":"2755_CR30","doi-asserted-by":"crossref","unstructured":"Ikawa Y, Enoki M, Tatsubori M (2012) Location inference using microblog messages. In: Proceedings of the 21st international conference on world wide web, pp 687\u2013690","DOI":"10.1145\/2187980.2188181"},{"key":"2755_CR31","doi-asserted-by":"publisher","first-page":"737","DOI":"10.1007\/s10479-017-2522-3","volume":"283","author":"JP Singh","year":"2019","unstructured":"Singh JP, Dwivedi YK, Rana NP, Kumar A, Kapoor KK (2019) Event classification and location prediction from tweets during disasters. Ann Oper Res 283:737\u2013757","journal-title":"Ann Oper Res"},{"key":"2755_CR32","doi-asserted-by":"crossref","unstructured":"Panasyuk A, Mehrotra KG, Yu ES-L (2020) Improving geocoding of a twitter user group using their account creation times and languages. In: 2020 IEEE\/ACM international conference on advances in social networks analysis and mining (ASONAM). IEEE, pp 460\u2013467","DOI":"10.1109\/ASONAM49781.2020.9381355"},{"issue":"2","key":"2755_CR33","doi-asserted-by":"publisher","first-page":"310","DOI":"10.1080\/13658816.2021.1947507","volume":"36","author":"X Hu","year":"2022","unstructured":"Hu X, Al-Olimat HS, Kersten J, Wiegmann M, Klan F, Sun Y, Fan H (2022) Gazpne: annotation-free deep learning for place name extraction from microblogs leveraging gazetteer and synthetic data by rules. Int J Geogr Inf Sci 36(2):310\u2013337","journal-title":"Int J Geogr Inf Sci"},{"key":"2755_CR34","doi-asserted-by":"crossref","unstructured":"Lutsai K, Lampert CH (2023) Predicting the geolocation of tweets using transformer models on customized data. arXiv preprint arXiv:2303.07865","DOI":"10.5311\/JOSIS.2024.29.295"},{"issue":"8","key":"2755_CR35","doi-asserted-by":"publisher","first-page":"1840","DOI":"10.1080\/13658816.2023.2213869","volume":"37","author":"V Tang","year":"2023","unstructured":"Tang V, Painho M (2023) Content-location relationships: a framework to explore correlations between space-based and place-based user-generated content. Int J Geogr Inf Sci 37(8):1840\u20131871","journal-title":"Int J Geogr Inf Sci"},{"key":"2755_CR36","doi-asserted-by":"crossref","unstructured":"Serere HN, Resch B, Havas CR (2023) Enhanced geocoding precision for location inference of tweet text using spacy, nominatim and google maps. a comparative analysis of the influence of data selection. PLoS ONE 18(3), 0282942","DOI":"10.1371\/journal.pone.0282942"},{"key":"2755_CR37","doi-asserted-by":"crossref","unstructured":"Sun K, Hu Y, Joseph K, Zhou RZ (2025) Galloc: a geoannotator for labeling location descriptions from disaster-related text messages. Int J Geograph Inf Sci 1\u201331","DOI":"10.1080\/13658816.2025.2464643"},{"key":"2755_CR38","doi-asserted-by":"publisher","DOI":"10.1016\/j.chb.2021.106722","volume":"119","author":"I Boutet","year":"2021","unstructured":"Boutet I, LeBlanc M, Chamberland JA, Collin CA (2021) Emojis influence emotional communication, social attributions, and information processing. Comput Hum Behav 119:106722","journal-title":"Comput Hum Behav"},{"issue":"6","key":"2755_CR39","doi-asserted-by":"publisher","first-page":"407","DOI":"10.3390\/ijgi10060407","volume":"10","author":"E Hauthal","year":"2021","unstructured":"Hauthal E, Dunkel A, Burghardt D (2021) Emojis as contextual indicants in location-based social media posts. ISPRS Int J Geo Inf 10(6):407","journal-title":"ISPRS Int J Geo Inf"},{"key":"2755_CR40","unstructured":"Google | Universal Sentence Encoder | Kaggle. https:\/\/tfhub.dev\/google\/universal-sentence-encoder\/4. Accessed: 2023-12-02 (n.d.)"},{"key":"2755_CR41","unstructured":"Mikolov T, Chen K, Corrado G, Dean J (2013) Efficient estimation of word representations in vector space. arXiv preprint arXiv:1301.3781"},{"key":"2755_CR42","doi-asserted-by":"crossref","unstructured":"Vanni L, Ducoffe M, Aguilar C, Precioso F, Mayaffre D (2018) Textual deconvolution saliency (TDS): a deep tool box for linguistic analysis. In: Proceedings of the 56th annual meeting of the association for computational linguistics (volume 1: long papers), pp 548\u2013557","DOI":"10.18653\/v1\/P18-1051"},{"key":"2755_CR43","unstructured":"Vaswani A, Shazeer N, Parmar N, Uszkoreit J, Jones L, Gomez AN, Kaiser \u0141, Polosukhin I (2017) Attention is all you need. In: Advances in neural information processing systems, 30"},{"key":"2755_CR44","doi-asserted-by":"publisher","DOI":"10.7910\/DVN\/LOTEGM","author":"HN Serere","year":"2022","unstructured":"Serere HN (2022) Replication Data for: Analysing the performance of a location inference method on various Twitter source distribution. Harvard Dataverse. https:\/\/doi.org\/10.7910\/DVN\/LOTEGM","journal-title":"Harvard Dataverse"},{"key":"2755_CR45","unstructured":"Devlin J, Chang M-W, Lee K, Toutanova K (2018) Bert: Pre-training of deep bidirectional transformers for language understanding. arXiv preprint arXiv:1810.04805"},{"key":"2755_CR46","doi-asserted-by":"crossref","unstructured":"Hegde V, Aswathi T, Sidharth R (2016) Student residential distance calculation using haversine formulation and visualization through googlemap for admission analysis. In: 2016 IEEE international conference on computational intelligence and computing research (ICCIC). IEEE, pp 1\u20135","DOI":"10.1109\/ICCIC.2016.7919699"}],"container-title":["Knowledge and Information Systems"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-026-02755-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/article\/10.1007\/s10115-026-02755-9","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/link.springer.com\/content\/pdf\/10.1007\/s10115-026-02755-9.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2026,4,17]],"date-time":"2026-04-17T04:43:34Z","timestamp":1776401014000},"score":1,"resource":{"primary":{"URL":"https:\/\/link.springer.com\/10.1007\/s10115-026-02755-9"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2026,4,17]]},"references-count":47,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2026,12]]}},"alternative-id":["2755"],"URL":"https:\/\/doi.org\/10.1007\/s10115-026-02755-9","relation":{},"ISSN":["0219-1377","0219-3116"],"issn-type":[{"value":"0219-1377","type":"print"},{"value":"0219-3116","type":"electronic"}],"subject":[],"published":{"date-parts":[[2026,4,17]]},"assertion":[{"value":"5 June 2025","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"6 December 2025","order":2,"name":"revised","label":"Revised","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"24 March 2026","order":3,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"17 April 2026","order":4,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}},{"order":1,"name":"Ethics","group":{"name":"EthicsHeading","label":"Declarations"}},{"value":"The authors declare no conflict of interest.","order":2,"name":"Ethics","group":{"name":"EthicsHeading","label":"Conflict of interest"}},{"value":"The research conducted in this study strictly adheres to ethical standards.","order":3,"name":"Ethics","group":{"name":"EthicsHeading","label":"Ethics approval"}},{"value":"All authors consent to all the terms and conditions for publication.","order":4,"name":"Ethics","group":{"name":"EthicsHeading","label":"Consent for publication"}}],"article-number":"128"}}