A novel algorithm for estimation of Twitter users location using public available information

Abbas, A. K., Bayat, O. and Nuri Ucan, O. 2017. Estimation of Twitter user’s nationality based on friends and follower’s information. Computers & Electrical Engineering, 66: 517–530, doi: 10.1016/j.compeleceng.2017.06.033. Abbas A. K. Bayat O. and Nuri Ucan O. 2017 Estimation of Twitter user’s nationality based on friends and follower’s information Computers & Electrical Engineering 66 517 – 530 , doi: 10.1016/j.compeleceng.2017.06.033 Open DOISearch in Google Scholar

Anber, H., Salah, A. and El-aziz, A. A. 2016. A literature review on Twitter data analysis. International Journal of Computer and Electrical Engineering 8(3): 241–249, doi: 10.17706/ijcee.2016.8.3.241-249. Anber H. Salah A. and El-aziz A. A. 2016 A literature review on Twitter data analysis International Journal of Computer and Electrical Engineering 8 (3 ): 241 – 249 , doi: 10.17706/ijcee.2016.8.3.241-249 Open DOISearch in Google Scholar

Atefeh, F. and Khreich, W. 2015. A survey of techniques for event detection in Twitter. Computational Intelligence 31: 132–164, doi: 10.1111/coin.12017. Atefeh F. and Khreich W. 2015 A survey of techniques for event detection in Twitter Computational Intelligence 31 132 – 164 , doi: 10.1111/coin.12017 Open DOISearch in Google Scholar

Bothos, E., Apostolou, D. and Mentzas, G. 2010. Using social media to predict future events with agent-based markets. IEEE Intelligent Systems 25(6): 50–58. Bothos E. Apostolou D. and Mentzas G. 2010 Using social media to predict future events with agent-based markets IEEE Intelligent Systems 25(6 ): 50 – 58 Search in Google Scholar

Brown, D. E., Abbasi, A. and Lau, R. Y. K. 2015. Predictive analytics. IEEE Intelligent Systems 30(2): 6–8. Brown D. E. Abbasi A. and Lau R. Y. K. 2015 Predictive analytics IEEE Intelligent Systems 30(2 ): 6 – 8 Search in Google Scholar

Chang, H. -W., Lee, D., Eltaher, M. and Lee, J. 2012. @ Phillies Tweeting from Philly? Predicting Twitter user locations with spatial word usage. pp. 111-118, doi: 10.1109/ASONAM.2012.29. Chang H. -W. Lee D. Eltaher M. and Lee J. 2012 @ Phillies Tweeting from Philly? Predicting Twitter user locations with spatial word usage pp. 111-118, doi: 10.1109/ASONAM.2012.29 Search in Google Scholar

Culotta, A., Ravi, N. K. and Cutler, J. 2015. Predicting the demographics of Twitter users from website traffic data. Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence, 72–78. Culotta A. Ravi N. K. and Cutler J. 2015 Predicting the demographics of Twitter users from website traffic data Proceedings of the Twenty-Ninth AAAI Conference on Artificial Intelligence 72 – 78 Search in Google Scholar

De Choudhury, M., Gamon, M., Counts, S. and Horvitz, E. 2013. Predicting depression via social media. ICWSM, 13: 1–10. De Choudhury M. Gamon M. Counts S. and Horvitz E. 2013 Predicting depression via social media ICWSM 13 1 – 10 Search in Google Scholar

Gentry, J. 2015. R Based Twitter Client Description Provides an interface to the Twitter web API, available at: http://lists.hexdump.org/listinfo.cgi/twitter-users-hexdump.org. Gentry J. 2015 R Based Twitter Client Description Provides an interface to the Twitter web API , available at: http://lists.hexdump.org/listinfo.cgi/twitter-users-hexdump.org Search in Google Scholar

Golbeck, J., Robles, C. and Turner, K. 2011. Predicting personality with social media. Conference on Human Factors in Computing Systems – Proceedings, 253–262, doi: 10.1145/1979742.1979614. Golbeck J. Robles C. and Turner K. 2011 Predicting personality with social media Conference on Human Factors in Computing Systems – Proceedings 253 – 262 , doi: 10.1145/1979742.1979614 Open DOISearch in Google Scholar

Hecht, B., Hong, L., Suh, B. and Chi, E. H. 2011. Tweets from Justin Bieber’s heart: the dynamics of the “Location” field in user profiles. CHI ‘11 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems, Vancouver, May 7–12, 237–246. Hecht B. Hong L. Suh B. and Chi E. H. 2011 Tweets from Justin Bieber’s heart: the dynamics of the “Location” field in user profiles CHI ‘11 Proceedings of the SIGCHI Conference on Human Factors in Computing Systems Vancouver May 7–12 237 – 246 Search in Google Scholar

Huang, W., Weber, I. and Vieweg, S. 2014. Inferring nationalities of Twitter users and studying inter-national linking. Proceedings of the 25th ACM Conference on Hypertext and Social Media, 237–242. Huang W. Weber I. and Vieweg S. 2014 Inferring nationalities of Twitter users and studying inter-national linking Proceedings of the 25th ACM Conference on Hypertext and Social Media 237 – 242 Search in Google Scholar

Jayanthi, N., Babu, B. V. and Rao, N. S. 2017. Survey on clinical prediction models for diabetes prediction. Journal of Big Data, 4(26), doi: 10.1186/s40537-017-0082-7. Jayanthi N. Babu B. V. and Rao N. S. 2017 Survey on clinical prediction models for diabetes prediction Journal of Big Data 4(26 ), doi: 10.1186/s40537-017-0082-7 Open DOISearch in Google Scholar

Kong, L., Liu, Z. and Huang, Y. 2014. SPOT: locating social media users based on social network context. Proceedings of the VLDB Endowment 7: 1681–1684. Kong L. Liu Z. and Huang Y. 2014 SPOT: locating social media users based on social network context Proceedings of the VLDB Endowment 7 1681 – 1684 Search in Google Scholar

Lazarus, R., Achrekar, H., Lazarus, R. and Park, W. C. 2011. Predicting flu trends using Twitter data. IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS, 702–707, doi: 10.1109/INFCOMW.2011.5928903. Lazarus R. Achrekar H. Lazarus R. and Park W. C. 2011 Predicting flu trends using Twitter data IEEE Conference on Computer Communications Workshops, INFOCOM WKSHPS 702 – 707 , doi: 10.1109/INFCOMW.2011.5928903 Open DOISearch in Google Scholar

Liu, H. 2013. Some computational challenges in mining social media. 2013 IEEE/ACM International Conference in Advances in Social Networks Analysis and Mining (ASONAM), Niagara Falls, August 25-28, doi: 10.1109/ASONAM.2013.6785672. Liu H. 2013 Some computational challenges in mining social media 2013 IEEE/ACM International Conference in Advances in Social Networks Analysis and Mining (ASONAM) Niagara Falls August 25-28 , doi: 10.1109/ASONAM.2013.6785672 Open DOISearch in Google Scholar

Mcgee, J., Caverlee, J. and Cheng, Z. 2013. Location prediction in social media based on tie strength. CIKM ‘13 Proceedings of the 22nd ACM International Conference on Information & Knowledge Management, 459–468. Mcgee J. Caverlee J. and Cheng Z. 2013 Location prediction in social media based on tie strength CIKM ‘13 Proceedings of the 22nd ACM International Conference on Information & Knowledge Management 459 – 468 Search in Google Scholar

Package based Twitter client description provides an interface to the Twitter web API. Version 1.1.8, February 20, 2015. Package based Twitter client description provides an interface to the Twitter web API. Version 1.1.8, February 20, 2015 Search in Google Scholar

Tsujioka, S., Kondo, A. and Watanabe, K. 2016. Estimation of residence information of Twitter users based on their posted messages: data for tourism development. International Journal of Research in Chemical, Metallurgical and Civil Engineering 3(1): 180–183. Tsujioka S. Kondo A. and Watanabe K. 2016 Estimation of residence information of Twitter users based on their posted messages: data for tourism development International Journal of Research in Chemical, Metallurgical and Civil Engineering 3(1 ): 180 – 183 Search in Google Scholar

Tufekci, Z. 2014. Big questions for social media big data: representativeness, validity and other methodological pitfalls. ICWSM 14, 505–514. Tufekci Z. 2014 Big questions for social media big data: representativeness, validity and other methodological pitfalls ICWSM 14 505 – 514 Search in Google Scholar

Tumasjan, A., Sprenger, T. O., Sandner, P. G. and Welpe, I. M. 2010. Predicting elections with Twitter: what 140 characters reveal about political sentiment. Conference: Proceedings of the Fourth International Conference on Weblogs and Social Media, ICWSM, Washington, DC, May 23-26, 178–185. Tumasjan A. Sprenger T. O. Sandner P. G. and Welpe I. M. 2010 Predicting elections with Twitter: what 140 characters reveal about political sentiment Conference: Proceedings of the Fourth International Conference on Weblogs and Social Media, ICWSM Washington, DC May 23-26 178 – 185 Search in Google Scholar

Volkova, S. and Yarowsky, D. (2014), “Improving gender prediction of social media users via weighted annotator rationales”, In NIPS 2014 Workshop on Personalization, San Diego, CA, December 8–13. Volkova S. and Yarowsky D. 2014 , “ Improving gender prediction of social media users via weighted annotator rationales ”, In NIPS 2014 Workshop on Personalization San Diego, CA December 8 – 13 Search in Google Scholar

Zhang, X., Fuehres, H. and Gloor, P. A. 2011. “Predicting stock market indicators through Twitter “I hope it is not as bad as I fear”, Procedia – Social and Behavioral Sciences 26: 55–62. Zhang X. Fuehres H. and Gloor P. A. 2011 . “ Predicting stock market indicators through Twitter “I hope it is not as bad as I fear ”, Procedia – Social and Behavioral Sciences 26 55 – 62 Search in Google Scholar