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47 BIBLIOGRAPHY Akvo , 2015 , Vanuatu HH Size and Water Point Functionality Visualization , http://akvo.cartodb.com/viz/b77c914a-cdc8-11e4-b131- 0e4fddd5de28/embed_map [Accessed March 10, 2015]w Batool, R., Khattak, A.M., Maqbool, J., & Lee, S., 2013. Precise Tweet Classification and Sentiment Analysis. Computer and Information Science (ICIS), 20133 IEEE/ACIS 12th Conference, pp.451-466. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumbe r=6607883 [Accessed March 10, 2015]. Bhuta, S., Doshi, A., Doshi, U., & Narvekar, M., 2014. A Review of Techniques for Sentiment Analysis of Twitter Data. Issues and Challenges in Intelligent Computing Techniques (ICICIT), 2014 International Conference, pp.583- 591. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumbe r=6781346 [Accessed March 10, 2015]. Boutet, A., Hyoungshick Kim, & Yoneki, E., 2012. What’s in Twitter: I Know What Parties are Popular and Who You are Supporting Now!. Advances in Social Network Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference, pp.132-139. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumbe r=6425772 [Accessed March 10, 2015]. Bradley T, 2015. The Unplumbed Depths of Government Data. Available at http://motherboard.vice.com/read/the-unplumbed-depths-of-government- data [Accessed March 10, 2015]. CartoDB, 2015, Tweet From Local and Tourist , https://satyanugraha1.cartodb.com/maps [Accessed March 10, 2015] Chen, X., Vorvoreanu, M., & Madhavan, K.P.C., 2014. Mining Social Media Data for Understanding Student’s Learning Experiences. IEEE Transactions on Learning Technologies, Vol. 7, No.3. Available at: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6406574 [Accessed March 10, 2015]. Cheng, Z., Caverlee, J., & Lee, K., 2010. You Are Where You Tweet: A Content- Based Approach to Geo-locating Twitter Users. Proceeding CIKM ’10 Proceedings of the 19th ACM International Conference on Information and Knowledge Management, pp. 759-768. Available at http://infolab.cse.tamu.edu/static/papers/cikm1184c-cheng.pdf [Accessed March 10, 2015]. Cho, S. H., & Kang, H. B., 2012. Statistical Text Analysis and Sentiment Classification in Social Media. Systems, Man, and Cybernetics (SMC), CLASSIFYING TWITTER USERS AS RESIDENTS OR TOURIST BASED ON TWITTER USER HISTORICAL DATA SATYA NUGRAHA, Edi Winarko, M.Sc., Ph.D Universitas Gadjah Mada, 2015 | Diunduh dari http://etd.repository.ugm.ac.id/

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BIBLIOGRAPHY

Akvo , 2015 , Vanuatu HH Size and Water Point Functionality Visualization , http://akvo.cartodb.com/viz/b77c914a-cdc8-11e4-b131-0e4fddd5de28/embed_map [Accessed March 10, 2015]w

Batool, R., Khattak, A.M., Maqbool, J., & Lee, S., 2013. Precise Tweet Classification and Sentiment Analysis. Computer and Information Science (ICIS), 20133 IEEE/ACIS 12th Conference, pp.451-466. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6607883 [Accessed March 10, 2015].

Bhuta, S., Doshi, A., Doshi, U., & Narvekar, M., 2014. A Review of Techniques for Sentiment Analysis of Twitter Data. Issues and Challenges in Intelligent Computing Techniques (ICICIT), 2014 International Conference, pp.583-591. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6781346 [Accessed March 10, 2015].

Boutet, A., Hyoungshick Kim, & Yoneki, E., 2012. What’s in Twitter: I Know What Parties are Popular and Who You are Supporting Now!. Advances in Social Network Analysis and Mining (ASONAM), 2012 IEEE/ACM International Conference, pp.132-139. Available at http://ieeexplore.ieee.org.ezproxy.ugm.ac.id/stamp/stamp.jsp?tp=&arnumber=6425772 [Accessed March 10, 2015].

Bradley T, 2015. The Unplumbed Depths of Government Data. Available at http://motherboard.vice.com/read/the-unplumbed-depths-of-government-data [Accessed March 10, 2015].

CartoDB, 2015, Tweet From Local and Tourist , https://satyanugraha1.cartodb.com/maps [Accessed March 10, 2015]

Chen, X., Vorvoreanu, M., & Madhavan, K.P.C., 2014. Mining Social Media Data for Understanding Student’s Learning Experiences. IEEE Transactions on Learning Technologies, Vol. 7, No.3. Available at: http://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=6406574 [Accessed March 10, 2015].

Cheng, Z., Caverlee, J., & Lee, K., 2010. You Are Where You Tweet: A Content-Based Approach to Geo-locating Twitter Users. Proceeding CIKM ’10 Proceedings of the 19th ACM International Conference on Information and Knowledge Management, pp. 759-768. Available at http://infolab.cse.tamu.edu/static/papers/cikm1184c-cheng.pdf [Accessed March 10, 2015].

Cho, S. H., & Kang, H. B., 2012. Statistical Text Analysis and Sentiment Classification in Social Media. Systems, Man, and Cybernetics (SMC),

CLASSIFYING TWITTER USERS AS RESIDENTS OR TOURIST BASED ON TWITTER USERHISTORICAL DATASATYA NUGRAHA, Edi Winarko, M.Sc., Ph.DUniversitas Gadjah Mada, 2015 | Diunduh dari http://etd.repository.ugm.ac.id/

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CLASSIFYING TWITTER USERS AS RESIDENTS OR TOURIST BASED ON TWITTER USERHISTORICAL DATASATYA NUGRAHA, Edi Winarko, M.Sc., Ph.DUniversitas Gadjah Mada, 2015 | Diunduh dari http://etd.repository.ugm.ac.id/