Optimization of Microblog Representation Using Deep Learning Approach
Author : K. H. WalseVolume 7 No.2 July-September 2018 pp 133 - 138
Abstract
Microblogging, as a new form of online communication in which users talk about their daily lives, to gather real-time news, opinion about people or share information by short posts, has become one of the most popular social networking services today, e.g. to stay in touch with friends . Finding proper representations of microblog texts is a challenging issue. The overview of microblog included how to extract information from microblog, also discuss about Microblogging and Twitter. This paper included existing research on Optimization of Microblog Representation by using existing techniques and methods as well as microblogging services.Current approaches, for microblog reduction are single indexing. In this work, we have proposed double indexing method for microblog reduction. We have used our own generated dataset for microblog reduction. We have collected tweets from real time twitter for both single and double indexing technique. Also, we have use LDA with Semantic Similarity algorithm. We compared our results with single indexing. Experimental results shows that double indexing gives better performance than single indexing. This may happen because we will show both original and reduced tweets, so it will be known to user which tweet are removed and relevant part shows as output. We have also compared our results with the state-of-art. The proposed double indexing gives better performance than existing 1-ROCA of improved online SVM technique.
Keywords
Microblogs, Twitter, Text representation, Sentiment analysis, Topic detection, Clustering, SVM
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References
[1] Lei Xu, Chunxiao Jiang, Senior Member, IEEE, Yong Ren, Member, IEEE, and Hsiao-Hwa Chen, Fellow, IEEE, “Microblog Dimensionality Reduction—A Deep Learning Approach”,
InKnowledge and Data Engineering, 2016, IEEE Transaction, Vol. 28, No.7,pp. 1779-1789, 2016.
[2] Zhi-Qiang Xian, Y. X. Zou and Xin Wang,“Sentiment Analysis of Chinese Micro-blog Using Vector Space Model”, 2014.
[3] Fotis Aisopos, George Papadakis, Konstantinos Tserpes and Theodora Varvarigou, “Content vs. Context for Sentiment Analysis:a Comparative Analysis over Microblogs”, In Proceedings of the 6th ACM, p. 12, pp. 187-196, ACM 2012.
[4] Xiaoqian Lui and Tingshao Zhu, “Deep learning for constructing microblog behavior representation to identify social media user’s personality”, In PeerJ Comput. Sci. 81, 2016, pp. 1-15, 2016.
[5] Bongwon Suh, Lichan Hong, Peter Pirolli, and Ed H. Chi , “Want to be Retweeted? Large Scale Analytics onFactors Impacting Retweet in Twitter Network.” IEEE International Conference on Social Computing, 2010, pp. 177 – 184, 2013.
[6] Xia Yan and Hua Zhao, “ Chinese Microblog Topic Detection Based on the Latent Semantic Analysis and Structural Property.” In JOURNAL OF NETWORKS, Vol. 8, No. 4, pp. 917-923, 2013.
[7] Xia Hu, Lei Tang and Huan Liu, “Enhancing Accessibility of Microblogging Messages Using Semantic Knowledge.” pp. 2465-2468, 2011.
[8] Mr. M. Vengateshwaran, Mrs. C. Ramyapriyadarsini and Ms. N. Valarmathi, “Efficient Deep Learning Approach for Dimensionality Reduction using Micro blogs from Big data”, IJRASET, Vol. 5, Issue 2, pp. 5-10,2017.
[9] Ms. Payal R. Rathi and Dr. K. H. Walse, “Survey on optimization of microblog Representation”, In Proceedings International Conference- EECCMC 2018, pp. 1-8, Jan 28 and Jan 29, 2018.
[10] Jiliang TANG, Xufei WANG, Huiji GAO, Xia HU, Huan LIU, Computer Science & Engineering, Arizona State University, Tempe, AZ 85281, USA“Enriching short text representation in microblog for clustering”, In Front. Comput. Sci., Vol. 6, No. 1, pp. 1-13, 2012.
[11] Kishor H. Walse, Rajiv V. Dharaskar and Vilas M. Thakare “A Study on the Effect of Adaptive Boosting on Performance of Classifiers for Human Activity Recognition”, InProceedings of the International Conferenceon Data Engineering and Communication Technology, Advances in Intelligent Systems and Computing, Vol. 469, pp. 419-429, 2017.
[12] Shrunkhala Satish Wankhede, Ms. S. A. Chhabria and Dr. R. V. Dharaskar “Contolling Mouse Cursor Using Eye Movement”, In IJAIEM, pp. 1-7, 2013.
[13] K. H. Waslse and D. R. Dhotre “Wireless Network: Performance Analysis of TCP”, Information Technology Journal, Vol. 6, No. 3, pp. 363-369, 2007.
[14] Hui Ning, Song Li, Fanhu Zeng and Li Xu “Research on Microblog Filtering Technology Based on Improved Online Support Vector Machine Model0”, IEEEInternational Conference on Mechatronics and Automation, pp. 2326- 2332, 2016.