{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,28]],"date-time":"2025-10-28T00:31:11Z","timestamp":1761611471331,"version":"3.37.3"},"reference-count":43,"publisher":"Springer Science and Business Media LLC","issue":"2","license":[{"start":{"date-parts":[[2019,2,7]],"date-time":"2019-02-07T00:00:00Z","timestamp":1549497600000},"content-version":"tdm","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"},{"start":{"date-parts":[[2019,2,7]],"date-time":"2019-02-07T00:00:00Z","timestamp":1549497600000},"content-version":"vor","delay-in-days":0,"URL":"http:\/\/www.springer.com\/tdm"}],"funder":[{"name":"SCOPE of the Ministry of Internal Affairs and Communications of Japan","award":["171507010"],"award-info":[{"award-number":["171507010"]}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"crossref","award":["16H01722"],"award-info":[{"award-number":["16H01722"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"crossref"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["17K12686"],"award-info":[{"award-number":["17K12686"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/501100001691","name":"Japan Society for the Promotion of Science","doi-asserted-by":"publisher","award":["17H01822"],"award-info":[{"award-number":["17H01822"]}],"id":[{"id":"10.13039\/501100001691","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["link.springer.com"],"crossmark-restriction":false},"short-container-title":["Pers Ubiquit Comput"],"published-print":{"date-parts":[[2019,4]]},"DOI":"10.1007\/s00779-019-01204-5","type":"journal-article","created":{"date-parts":[[2019,2,7]],"date-time":"2019-02-07T16:37:51Z","timestamp":1549557471000},"page":"233-247","update-policy":"https:\/\/doi.org\/10.1007\/springer_crossmark_policy","source":"Crossref","is-referenced-by-count":5,"title":["Twitter-based traffic delay detection based on topic propagation analysis using railway network topology"],"prefix":"10.1007","volume":"23","author":[{"ORCID":"https:\/\/orcid.org\/0000-0001-8181-3465","authenticated-orcid":false,"given":"Yuanyuan","family":"Wang","sequence":"first","affiliation":[]},{"given":"Panote","family":"Siriaraya","sequence":"additional","affiliation":[]},{"given":"Yukiko","family":"Kawai","sequence":"additional","affiliation":[]},{"given":"Toyokazu","family":"Akiyama","sequence":"additional","affiliation":[]}],"member":"297","published-online":{"date-parts":[[2019,2,7]]},"reference":[{"key":"1204_CR1","unstructured":"Twitter: \n                    http:\/\/twitter.com\/"},{"key":"1204_CR2","unstructured":"Foursquare: \n                    https:\/\/foursquare.com\/"},{"key":"1204_CR3","unstructured":"Tumblr: \n                    https:\/\/www.tumblr.com\/"},{"key":"1204_CR4","unstructured":"Jorudan: \n                    https:\/\/world.jorudan.co.jp\/mln\/en\/?sub_lang=ja"},{"key":"1204_CR5","unstructured":"Tokyo Metro Subway Map: \n                    http:\/\/www.tokyometro.jp\/en\/subwaymap\/pdf\/rosen_en_1702.pdf"},{"key":"1204_CR6","unstructured":"Twitter Streaming API: \n                    https:\/\/dev.twitter.com\/streaming\/overview"},{"key":"1204_CR7","unstructured":"Google Places API v3: \n                    https:\/\/developers.google.com\/place"},{"key":"1204_CR8","unstructured":"World Urbanization Prospects (2014) The 2014 revision population database, vol ST\/ESA\/SE.A\/352. United Nations"},{"key":"1204_CR9","doi-asserted-by":"publisher","unstructured":"Ardon S, Bagchi A, Mahanti A, Ruhela A, Seth A, Tripathy RM, Triukose S (2013) Spatio-temporal and events based analysis of topic popularity in twitter. In: Proceedings of the 22nd ACM international conference on information & knowledge management, CIKM \u201913, pp 219\u2013228. \n                    https:\/\/doi.org\/10.1145\/2505515.2505525\n                    \n                  . \n                    http:\/\/doi.acm.org\/10.1145\/2505515.2505525","DOI":"10.1145\/2505515.2505525"},{"issue":"3","key":"1204_CR10","doi-asserted-by":"publisher","first-page":"176","DOI":"10.5829\/idosi.ejas.2016.8.3.23003","volume":"8","author":"R Auxilia","year":"2016","unstructured":"Auxilia R, Gandhi M (2016) Earthquake reporting system development by tweet analysis with approach earthquake alarm systems. European Journal of Applied Sciences 8(3):176\u2013180. \n                    https:\/\/doi.org\/10.5829\/idosi.ejas.2016.8.3.23003","journal-title":"European Journal of Applied Sciences"},{"issue":"10","key":"1204_CR11","first-page":"1","volume":"19","author":"J Carvalho","year":"2017","unstructured":"Carvalho J, Marques M, Costeira JP (2017) Understanding people flow in transportation hubs. IEEE Trans Intell Transp Syst 19(10):1\u201310","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"1204_CR12","doi-asserted-by":"publisher","unstructured":"Daly EM, Lecue F, Bicer V (2013) Westland row why so slow?: Fusing social media and linked data sources for understanding real-time traffic conditions. In: Proceedings of the 2013 international conference on intelligent user interfaces, IUI \u201913, pp 203\u2013212. \n                    https:\/\/doi.org\/10.1145\/2449396.2449423","DOI":"10.1145\/2449396.2449423"},{"issue":"4","key":"1204_CR13","doi-asserted-by":"publisher","first-page":"2269","DOI":"10.1109\/TITS.2015.2404431","volume":"16","author":"E D\u2019Andrea","year":"2015","unstructured":"D\u2019Andrea E, Ducange P, Lazzerini B, Marcelloni F (2015) Real-time detection of traffic from twitter stream analysis. IEEE Trans Intell Transp Syst 16(4):2269\u20132283. \n                    https:\/\/doi.org\/10.1109\/TITS.2015.2404431","journal-title":"IEEE Trans Intell Transp Syst"},{"issue":"C","key":"1204_CR14","doi-asserted-by":"publisher","first-page":"551","DOI":"10.1016\/j.compeleceng.2016.06.012","volume":"58","author":"G Dong","year":"2017","unstructured":"Dong G, Yang W, Zhu F, Wang W (2017) Discovering burst patterns of burst topic in twitter. Comput Electr Eng 58(C):551\u2013559. \n                    https:\/\/doi.org\/10.1016\/j.compeleceng.2016.06.012","journal-title":"Comput Electr Eng"},{"key":"1204_CR15","doi-asserted-by":"publisher","first-page":"424","DOI":"10.1016\/j.chb.2014.05.005","volume":"41","author":"I Eleta","year":"2014","unstructured":"Eleta I, Golbeck J (2014) Multilingual use of twitter: social networks at the language frontier. Comput Hum Behav 41:424\u2013432","journal-title":"Comput Hum Behav"},{"key":"1204_CR16","doi-asserted-by":"publisher","unstructured":"Endarnoto SK, Pradipta S, Nugroho AS, Purnama J (2011) Traffic condition information extraction & visualization from social media twitter for android mobile application. In: Proceedings of the international conference on electronics engineering and informatics, ICEEI \u201911, pp 1\u20134. \n                    https:\/\/doi.org\/10.1109\/ICEEI.2011.6021743","DOI":"10.1109\/ICEEI.2011.6021743"},{"issue":"1","key":"1204_CR17","doi-asserted-by":"publisher","first-page":"11","DOI":"10.1145\/2674026.2674029","volume":"16","author":"O Goonetilleke","year":"2014","unstructured":"Goonetilleke O, Sellis T, Zhang X, Sathe S (2014) Twitter analytics: a big data management perspective. ACM SIGKDD Explorations Newsletter 16(1):11\u201320. \n                    https:\/\/doi.org\/10.1145\/2674026.2674029\n                    \n                  . \n                    http:\/\/doi.acm.org\/10.1145\/2674026.2674029","journal-title":"ACM SIGKDD Explorations Newsletter"},{"key":"1204_CR18","doi-asserted-by":"publisher","unstructured":"G\u00fcnnemann N, Pfeffer J (2015) Finding non-redundant multi-word events on twitter. In: Proceedings of the 2015 IEEE\/ACM international conference on advances in social networks analysis and mining 2015, ASONAM \u201915, pp 520\u2013525. \n                    https:\/\/doi.org\/10.1145\/2808797.2809390","DOI":"10.1145\/2808797.2809390"},{"key":"1204_CR19","doi-asserted-by":"publisher","unstructured":"Gutierrez C, Figueiras P, Oliveira P, Costa R, Jardim-Goncalves R (2015) Twitter mining for traffic events detection. In: IEEE science and information conference 2015, SAI 2015. \n                    https:\/\/doi.org\/10.1109\/SAI.2015.7237170","DOI":"10.1109\/SAI.2015.7237170"},{"key":"1204_CR20","doi-asserted-by":"publisher","unstructured":"Itoh M, Yoshinaga N, Toyoda M (2016) Spatio-temporal event visualization from a geo-parsed microblog stream. In: Companion publication of the 21st international conference on intelligent user interfaces, IUI \u201916 Companion, pp 58\u201361. \n                    https:\/\/doi.org\/10.1145\/2876456.2879486\n                    \n                  . \n                    http:\/\/doi.acm.org\/10.1145\/2876456.2879486","DOI":"10.1145\/2876456.2879486"},{"key":"1204_CR21","doi-asserted-by":"publisher","first-page":"712","DOI":"10.1016\/j.trpro.2017.12.091","volume":"27","author":"B Kabalan","year":"2017","unstructured":"Kabalan B, Leurent F, Christoforou Z, Dubroca-Voisin M (2017) Framework for centralized and dynamic pedestrian management in railway stations. Transportation Research Procedia 27:712\u2013719. \n                    https:\/\/doi.org\/10.1016\/j.trpro.2017.12.091","journal-title":"Transportation Research Procedia"},{"issue":"1","key":"1204_CR22","doi-asserted-by":"publisher","first-page":"48","DOI":"10.4018\/IJSWIS.2017010105","volume":"13","author":"F Kalloubi","year":"2017","unstructured":"Kalloubi F, Nfaoui EH, El Beqqali O (2017) Harnessing semantic features for large-scale content-based hashtag recommendations on microblogging platforms. International Journal on Semantic Web & Information Systems 13(1):48\u201367. \n                    https:\/\/doi.org\/10.4018\/IJSWIS.2017010104","journal-title":"International Journal on Semantic Web & Information Systems"},{"key":"1204_CR23","doi-asserted-by":"publisher","unstructured":"Lee R, Sumiya K (2010) Measuring geographical regularities of crowd behaviors for twitter-based geo-social event detection. In: Proceedings of the 2nd ACM SIGSPATIAL international workshop on location based social networks, LBSN \u201910. ACM, New York, pp 1\u201310. \n                    https:\/\/doi.org\/10.1145\/1867699.1867701","DOI":"10.1145\/1867699.1867701"},{"issue":"4","key":"1204_CR24","doi-asserted-by":"publisher","first-page":"321","DOI":"10.1007\/s11280-011-0120-x","volume":"14","author":"R Lee","year":"2011","unstructured":"Lee R, Wakamiya S, Sumiya K (2011) Discovery of unusual regional social activities using geo-tagged microblogs. World Wide Web 14(4):321\u2013349. \n                    https:\/\/doi.org\/10.1007\/s11280-011-0120-x","journal-title":"World Wide Web"},{"key":"1204_CR25","doi-asserted-by":"publisher","unstructured":"Liu M, Fu K, Lu CT, Chen G, Wang H (2014) A search and summary application for traffic events detection based on twitter data. In: Proceedings of the 22nd ACM SIGSPATIAL international conference on advances in geographic information systems, SIGSPATIAL \u201914, pp 549\u2013552. \n                    https:\/\/doi.org\/10.1145\/2666310.2666366\n                    \n                  . \n                    http:\/\/doi.acm.org\/10.1145\/2666310.2666366","DOI":"10.1145\/2666310.2666366"},{"key":"1204_CR26","doi-asserted-by":"publisher","unstructured":"Mallela D, Ahlers D, Pera MS (2017) Mining twitter features for event summarization and rating. In: Proceedings of the international conference on web intelligence, WI \u201917, pp 615\u2013622. \n                    https:\/\/doi.org\/10.1145\/3106426.3106487","DOI":"10.1145\/3106426.3106487"},{"issue":"1","key":"1204_CR27","first-page":"53","volume":"64","author":"M Morioka","year":"2015","unstructured":"Morioka M, Kuramochi K, Mishina Y, Akiyama T, Taniguchi N (2015) City management platform using big data from people and traffic flows. Hitachi Review 64(1):53","journal-title":"Hitachi Review"},{"issue":"1","key":"1204_CR28","doi-asserted-by":"publisher","first-page":"61","DOI":"10.1007\/s11280-016-0417-x","volume":"20","author":"R Nugroho","year":"2017","unstructured":"Nugroho R, Zhao W, Yang J, Paris C, Nepal S (2017) Using time-sensitive interactions to improve topic derivation in twitter. World Wide Web 20(1):61\u201387. \n                    https:\/\/doi.org\/10.1007\/s11280-016-0417-x","journal-title":"World Wide Web"},{"issue":"3","key":"1204_CR29","doi-asserted-by":"publisher","first-page":"187","DOI":"10.3390\/mca14030187","volume":"14","author":"C Ozkurt","year":"2009","unstructured":"Ozkurt C, Camci F (2009) Automatic traffic density estimation and vehicle classification for traffic surveillance systems using neural networks. Mathematical and Computational Application 14(3):187\u2013196. \n                    https:\/\/doi.org\/10.3390\/mca14030187","journal-title":"Mathematical and Computational Application"},{"issue":"3","key":"1204_CR30","doi-asserted-by":"publisher","first-page":"1","DOI":"10.1007\/s10115-016-0997-x","volume":"51","author":"F Pla","year":"2016","unstructured":"Pla F, Hurtado LF (2016) Language identification of multilingual posts from twitter: a case study. Knowl Inf Syst 51(3):1\u201325. \n                    https:\/\/doi.org\/10.1007\/s10115-016-0997-x","journal-title":"Knowl Inf Syst"},{"key":"1204_CR31","doi-asserted-by":"publisher","unstructured":"Raghavi KC, Chinnakotla MK, Shrivastava M (2015) \u201canswer ka type kya he?\u201d: Learning to classify questions in code-mixed language. In: Proceedings of the 24th international conference on World Wide Web, WWW \u201915 companion. ACM, New York, pp 853\u2013858. \n                    https:\/\/doi.org\/10.1145\/2740908.2743006","DOI":"10.1145\/2740908.2743006"},{"key":"1204_CR32","doi-asserted-by":"publisher","unstructured":"Ritter A, Mausam, Etzioni O, Clark S (2012) Open domain event extraction from twitter. In: Proceedings of the 18th ACM SIGKDD international conference on knowledge discovery and data mining, KDD \u201912, pp 1104\u20131112. \n                    https:\/\/doi.org\/10.1145\/2339530.2339704\n                    \n                  . \n                    http:\/\/doi.acm.org\/10.1145\/2339530.2339704","DOI":"10.1145\/2339530.2339704"},{"issue":"4","key":"1204_CR33","doi-asserted-by":"publisher","first-page":"919","DOI":"10.1109\/TKDE.2012.29","volume":"25","author":"T Sakaki","year":"2013","unstructured":"Sakaki T, Okazaki M, Matsuo Y (2013) Tweet analysis for real-time event detection and earthquake reporting system development. IEEE Trans Knowl Data Eng 25(4):919\u2013931. \n                    https:\/\/doi.org\/10.1109\/TKDE.2012.29","journal-title":"IEEE Trans Knowl Data Eng"},{"key":"1204_CR34","doi-asserted-by":"publisher","unstructured":"Stilo G, Velardi P (2014) Time makes sense: event discovery in twitter using temporal similarity. In: Proceeidngs of the 2014 IEEE\/WIC\/ACM international joint conferences on Web Intelligence (WI) and intelligent agent technologies (IAT) - Volume 02, WI-IAT \u201914, pp 186\u2013193. \n                    https:\/\/doi.org\/10.1109\/WI-IAT.2014.97","DOI":"10.1109\/WI-IAT.2014.97"},{"issue":"4","key":"1204_CR35","first-page":"136","volume":"7","author":"B Sureesha","year":"2016","unstructured":"Sureesha B, Priyadarshini V (2016) Monitoring and analysis of dynamic traffic analyzer using twitter. IEEE Trans Intell Transp Syst 7(4):136\u2013139","journal-title":"IEEE Trans Intell Transp Syst"},{"key":"1204_CR36","doi-asserted-by":"crossref","unstructured":"Wakamiya S, Lee R, Sumiya K (2011) Crowd-powered tv viewing rates: measuring relevancy between tweets and tv programs. In: International conference on database systems for advanced applications. Springer, pp 390\u2013401","DOI":"10.1007\/978-3-642-20244-5_37"},{"key":"1204_CR37","doi-asserted-by":"publisher","unstructured":"Wakamiya S, Lee R, Sumiya K (2011) Towards better tv viewing rates: Exploiting crowd\u2019s media life logs over twitter for tv rating. In: Proceedings of the 5th international conference on ubiquitous information management and communication, ICUIMC \u201911. ACM, New York, pp 39:1\u201339:10. \n                    https:\/\/doi.org\/10.1145\/1968613.1968661","DOI":"10.1145\/1968613.1968661"},{"issue":"4","key":"1204_CR38","doi-asserted-by":"publisher","first-page":"40:1","DOI":"10.1145\/3057281","volume":"35","author":"S Wang","year":"2017","unstructured":"Wang S, Zhang X, Cao J, He L, Stenneth L, Yu PS, Li Z, Huang Z (2017) Computing urban traffic congestions by incorporating sparse gps probe data and social media data. ACM Trans Inf Syst (TOIS) 35 (4):40:1\u201340:30. \n                    https:\/\/doi.org\/10.1145\/3057281","journal-title":"ACM Trans Inf Syst (TOIS)"},{"key":"1204_CR39","doi-asserted-by":"publisher","unstructured":"Wang Y, Yasui G, Hosokawa Y, Kawai Y, Akiyama T, Sumiya K (2014) Location-based microblog viewing system synchronized with web pages. In: 2014 IEEE 33rd international symposium on reliable distributed systems workshops (SRDSW). IEEE, pp 70\u201375. \n                    https:\/\/doi.org\/10.1109\/SRDSW.2014.18","DOI":"10.1109\/SRDSW.2014.18"},{"key":"1204_CR40","doi-asserted-by":"publisher","unstructured":"Wang Y, Yasui G, Kawai Y, Akiyama T, Sumiya K, Ishikawa Y (2016) Dynamic mapping of dense geo-tweets and web pages based on spatio-temporal analysis. In: Proceedings of the 31st annual ACM symposium on applied computing, SAC \u201916, pp 1170\u20131173. \n                    https:\/\/doi.org\/10.1145\/2851613.2851985\n                    \n                  . \n                    http:\/\/doi.acm.org\/10.1145\/2851613.2851985","DOI":"10.1145\/2851613.2851985"},{"issue":"1","key":"1204_CR41","doi-asserted-by":"publisher","first-page":"41","DOI":"10.1080\/15472450.2013.773225","volume":"18","author":"Y Yuan","year":"2014","unstructured":"Yuan Y, Lint HV, Wageningen-Kessels FV, Hoogendoorn S (2014) Network-wide traffic state estimation using loop detector and floating car data. J Intell Transp Syst Technol Plann Oper 18(1):41\u201350. \n                    https:\/\/doi.org\/10.1080\/15472450.2013.773225","journal-title":"J Intell Transp Syst Technol Plann Oper"},{"key":"1204_CR42","doi-asserted-by":"publisher","unstructured":"Zhao F, Zhu Y, Jin H, Yang LT (2016) A personalized hashtag recommendation approach using lda-based topic model in microblog environment, vol 65, pp 196\u2013206. \n                    https:\/\/doi.org\/10.1016\/j.future.2015.10.012","DOI":"10.1016\/j.future.2015.10.012"},{"issue":"1","key":"1204_CR43","doi-asserted-by":"publisher","first-page":"16","DOI":"10.1109\/TBDATA.2015.2465959","volume":"1","author":"Y Zheng","year":"2015","unstructured":"Zheng Y (2015) Methodologies for cross-domain data fusion: an overview. IEEE Transactions on Big Data 1 (1):16\u201334. \n                    https:\/\/doi.org\/10.1109\/TBDATA.2015.2465959","journal-title":"IEEE Transactions on Big Data"}],"container-title":["Personal and Ubiquitous Computing"],"original-title":[],"language":"en","link":[{"URL":"http:\/\/link.springer.com\/article\/10.1007\/s00779-019-01204-5\/fulltext.html","content-type":"text\/html","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00779-019-01204-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"text-mining"},{"URL":"http:\/\/link.springer.com\/content\/pdf\/10.1007\/s00779-019-01204-5.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2020,5,14]],"date-time":"2020-05-14T07:42:20Z","timestamp":1589442140000},"score":1,"resource":{"primary":{"URL":"http:\/\/link.springer.com\/10.1007\/s00779-019-01204-5"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2019,2,7]]},"references-count":43,"journal-issue":{"issue":"2","published-print":{"date-parts":[[2019,4]]}},"alternative-id":["1204"],"URL":"https:\/\/doi.org\/10.1007\/s00779-019-01204-5","relation":{},"ISSN":["1617-4909","1617-4917"],"issn-type":[{"type":"print","value":"1617-4909"},{"type":"electronic","value":"1617-4917"}],"subject":[],"published":{"date-parts":[[2019,2,7]]},"assertion":[{"value":"2 May 2018","order":1,"name":"received","label":"Received","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"28 January 2019","order":2,"name":"accepted","label":"Accepted","group":{"name":"ArticleHistory","label":"Article History"}},{"value":"7 February 2019","order":3,"name":"first_online","label":"First Online","group":{"name":"ArticleHistory","label":"Article History"}}]}}