Sentiment analysis of twitter data, Proceedings of the workshop on languages in social media, pp.30-38, 2011. ,
Mining association rules between sets of items in large databases, Acm sigmod record, pp.207-216, 1993. ,
DOI : 10.1145/170036.170072
URL : http://arbor.ee.ntu.edu.tw/~chyun/dmpaper/agrama93.pdf
Interpreting Reputation Through Frequent Named Entities in Twitter, International Conference on Web Information Systems Engineering, pp.49-56, 2017. ,
DOI : 10.1007/978-3-319-08608-8_9
URL : https://hal.archives-ouvertes.fr/hal-01611593
Product reputation trend extraction from twitter. Social Networking, 2014. ,
DOI : 10.4236/sn.2014.34024
URL : http://www.scirp.org/journal/PaperDownload.aspx?paperID=48257
Modeling public mood and emotion: Twitter sentiment and socio-economic phenomena, ICWSM, vol.11, pp.450-453, 2011. ,
Social Network Analysis and Mining for Business Applications, ACM Transactions on Intelligent Systems and Technology, vol.2, issue.3, pp.1-2237, 2011. ,
DOI : 10.1145/1961189.1961194
Measuring user influence in twitter: The million follower fallacy, Icwsm, vol.10, pp.10-1730, 2010. ,
Entity discovery and assignment for opinion mining applications, Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '09, pp.1125-1134, 2009. ,
DOI : 10.1145/1557019.1557141
Sentiwordnet: A publicly available lexical resource for opinion mining, Proceedings of LREC, pp.417-422, 2006. ,
Sampling online social networks, ACM SIGCOMM Computer Communication Review, vol.44, issue.4, pp.127-128, 2014. ,
DOI : 10.1145/1851182.1851231
URL : https://hal.archives-ouvertes.fr/hal-01096980
On sampling the wisdom of crowds, Proceedings of the 22nd ACM international conference on Conference on information & knowledge management, CIKM '13, pp.1739-1744, 2013. ,
DOI : 10.1145/2505515.2505615
Walking in Facebook: A Case Study of Unbiased Sampling of OSNs, 2010 Proceedings IEEE INFOCOM, pp.1-9, 2010. ,
DOI : 10.1109/INFCOM.2010.5462078
Scalable, generic, and adaptive systems for focused crawling, Proceedings of the 25th ACM conference on Hypertext and social media, HT '14, pp.35-45, 2014. ,
DOI : 10.1145/2631775.2631795
URL : https://hal.archives-ouvertes.fr/hal-01069821
Szte-nlp: Sentiment detection on twitter messages, Second Joint Conference on Lexical and Computational Semantics, pp.549-553, 2013. ,
Sentiment Lexicon Creation from Lexical Resources, International Conference on Business Information Systems, pp.185-196, 2011. ,
DOI : 10.3115/1218955.1218990
Exploiting emoticons in sentiment analysis, Proceedings of the 28th Annual ACM Symposium on Applied Computing, SAC '13, pp.703-710, 2013. ,
DOI : 10.1145/2480362.2480498
Sampling from large graphs, Proceedings of the 12th ACM SIGKDD international conference on Knowledge discovery and data mining , KDD '06, pp.631-636, 2006. ,
DOI : 10.1145/1150402.1150479
Processing and visualizing the data in tweets, ACM SIGMOD Record, vol.40, issue.4, pp.21-27, 2012. ,
DOI : 10.1145/2094114.2094120
Entity-centric topic-oriented opinion summarization in twitter, Proceedings of the 18th ACM SIGKDD international conference on Knowledge discovery and data mining, KDD '12, pp.379-387, 2012. ,
DOI : 10.1145/2339530.2339592
Discovering users' topics of interest on twitter, Proceedings of the fourth workshop on Analytics for noisy unstructured text data, AND '10, pp.73-80, 2010. ,
DOI : 10.1145/1871840.1871852
Walk, not wait, Proceedings of the VLDB Endowment, pp.678-689, 2015. ,
DOI : 10.14778/2735703.2735707
analysis of sampling algorithms for twitter, Proc. of the 24th Int. Joint Conf. on Artificial Intelligence (IJCAI 2015), pp.967-973, 2015. ,
Semantic Sentiment Analysis of Twitter, International Semantic Web Conference, pp.508-524, 2012. ,
DOI : 10.1007/978-3-642-35176-1_32
Sentiment in Twitter events, Journal of the American Society for Information Science and Technology, vol.22, issue.2, pp.406-418, 2011. ,
DOI : 10.1111/j.1467-8640.2006.00275.x
Sentiment strength detection for the social web, Journal of the American Society for Information Science and Technology, vol.6458, issue.2, pp.163-173, 2012. ,
DOI : 10.1007/978-3-642-17187-1_43
Topic-Dependent Sentiment Classification on Twitter, European Conference on Information Retrieval, pp.441-446, 2015. ,
DOI : 10.1007/978-3-319-16354-3_48
Understanding Graph Sampling Algorithms for Social Network Analysis, 2011 31st International Conference on Distributed Computing Systems Workshops, pp.123-128, 2011. ,
DOI : 10.1109/ICDCSW.2011.34
URL : http://user.informatik.uni-goettingen.de/%7Eychen/graph_sampling_simplex11.pdf
Sampling online social networks via heterogeneous statistics, 2015 IEEE Conference on Computer Communications (INFOCOM), pp.2587-2595, 2015. ,
DOI : 10.1109/INFOCOM.2015.7218649
URL : http://arxiv.org/pdf/1501.02905
Topic sentiment analysis in twitter, Proceedings of the 20th ACM international conference on Information and knowledge management, CIKM '11, pp.1031-1040, 2011. ,
DOI : 10.1145/2063576.2063726
Improving twitter sentiment analysis with topicbased mixture modeling and semi-supervised training, pp.434-439, 2014. ,
DOI : 10.3115/v1/p14-2071
URL : https://doi.org/10.3115/v1/p14-2071
SharkDB: an in-memory column-oriented storage for trajectory analysis, World Wide Web, vol.6, issue.2, pp.455-485, 2018. ,
DOI : 10.1109/ICDE.2002.994784
Interactive Top-k Spatial Keyword queries, 2015 IEEE 31st International Conference on Data Engineering, pp.423-434, 2015. ,
DOI : 10.1109/ICDE.2015.7113303
Popularity-aware spatial keyword search on activity trajectories, World Wide Web, vol.38, issue.2, pp.749-773, 2017. ,
DOI : 10.1145/1132956.1132959
Sentiment analysis on twitter through topicbased lexicon expansion, Australasian Database Conference, pp.98-109, 2014. ,
DOI : 10.1007/978-3-319-08608-8_9