=Paper=
{{Paper
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|storemode=property
|title=None
|pdfUrl=https://ceur-ws.org/Vol-1625/inv1.pdf
|volume=Vol-1625
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==None==
<pdf width="1500px">https://ceur-ws.org/Vol-1625/inv1.pdf</pdf>
<pre>
 Sentiment Analysis of Twitter Messages: Tasks,
            Approaches and Results

                              Natalia Loukachevitch

           Research Computing Center, Moscow State University, Russia



      Abstract. Microblog messages became a very popular tool for commu-
      nication between people. Authors of the messages write about their life,
      convey their opinions on various topics including political and religious
      views, products and services, etc. Thus, microblogging sites as Twitter
      become valuable sources of information about peoples’s opinions and sen-
      timents. Approaches for extracting these opinions and their aggregation
      are actively studied.
      In my talk I consider sentiment analysis tasks proposed for processing
      Twitter messages and the existing approaches including neural networks,
      which allowed improving the existing results during last year. Also I
      present results of the Russian evaluation of sentiment analysis systems
      (SentiRuEval) organized in 2015-2016.

      Keywords: sentiments analysis, microblog messages, opinion mining


References
1. Loukachevitch, N.V., Rubtsova, Y.: Entity-oriented sentiment analysis of tweets:
   Results and problems. In: Text, Speech, and Dialogue - 18th International Confer-
   ence, TSD 2015, Pilsen,Czech Republic, September 14-17, 2015, Proceedings. (2015)
   551–559
2. Loukachevitch, N., Blinov, P., Kotelnikov, E., Rubtsova, Y., Ivanov, V., V, V.,
   Tutubalina, E.: Sentirueval: testing object-oriented sentiment analysis systems in
   russian. In: Proceedings of International Conference Dialog. Volume 2. (2015) 3–13

</pre>