Using Sentiment Analysis of Twitter Data for Determining Popularity of City Locations
Abstract
The paper considers mining and analyzing data generated by Twitter social network, regarding content classification, language determination and sentiment analysis of tweets. Analyzes are based on geospatial tweets collected in timespan of four months within region Vracar in Belgrade, Serbia. All of collected data is first being preprocessed, filtered and classified by given criteria, by using "Twitter search engine" (TSE) application, that has been upgraded in order to detect tweet language and execute sentiment analysis of the tweets written in English. This type of analysis can be used for determining popularity of city locations of interest and public spaces in general.
Keywords:
Geospatial data / Natural language processing / Sentiment analysis and opinion mining / Twitter social networkSource:
ICT innovations 2016: cognitive functions and next generation ICT systems, 2018, 665, 156-164Publisher:
- Springer Verlag
DOI: 10.1007/978-3-319-68855-8_15
ISSN: 2194-5357
WoS: 000448429600015
Scopus: 2-s2.0-85031736676
Institution/Community
Arhitektonski fakultetTY - CONF AU - Dinkić, Nikola AU - Džaković, Nikola AU - Joković, Jugoslav AU - Stoimenov, L. AU - Đukić, Aleksandra PY - 2018 UR - https://raf.arh.bg.ac.rs/handle/123456789/298 AB - The paper considers mining and analyzing data generated by Twitter social network, regarding content classification, language determination and sentiment analysis of tweets. Analyzes are based on geospatial tweets collected in timespan of four months within region Vracar in Belgrade, Serbia. All of collected data is first being preprocessed, filtered and classified by given criteria, by using "Twitter search engine" (TSE) application, that has been upgraded in order to detect tweet language and execute sentiment analysis of the tweets written in English. This type of analysis can be used for determining popularity of city locations of interest and public spaces in general. PB - Springer Verlag C3 - ICT innovations 2016: cognitive functions and next generation ICT systems T1 - Using Sentiment Analysis of Twitter Data for Determining Popularity of City Locations VL - 665 SP - 156 EP - 164 DO - 10.1007/978-3-319-68855-8_15 ER -
@conference{ author = "Dinkić, Nikola and Džaković, Nikola and Joković, Jugoslav and Stoimenov, L. and Đukić, Aleksandra", year = "2018", abstract = "The paper considers mining and analyzing data generated by Twitter social network, regarding content classification, language determination and sentiment analysis of tweets. Analyzes are based on geospatial tweets collected in timespan of four months within region Vracar in Belgrade, Serbia. All of collected data is first being preprocessed, filtered and classified by given criteria, by using "Twitter search engine" (TSE) application, that has been upgraded in order to detect tweet language and execute sentiment analysis of the tweets written in English. This type of analysis can be used for determining popularity of city locations of interest and public spaces in general.", publisher = "Springer Verlag", journal = "ICT innovations 2016: cognitive functions and next generation ICT systems", title = "Using Sentiment Analysis of Twitter Data for Determining Popularity of City Locations", volume = "665", pages = "156-164", doi = "10.1007/978-3-319-68855-8_15" }
Dinkić, N., Džaković, N., Joković, J., Stoimenov, L.,& Đukić, A.. (2018). Using Sentiment Analysis of Twitter Data for Determining Popularity of City Locations. in ICT innovations 2016: cognitive functions and next generation ICT systems Springer Verlag., 665, 156-164. https://doi.org/10.1007/978-3-319-68855-8_15
Dinkić N, Džaković N, Joković J, Stoimenov L, Đukić A. Using Sentiment Analysis of Twitter Data for Determining Popularity of City Locations. in ICT innovations 2016: cognitive functions and next generation ICT systems. 2018;665:156-164. doi:10.1007/978-3-319-68855-8_15 .
Dinkić, Nikola, Džaković, Nikola, Joković, Jugoslav, Stoimenov, L., Đukić, Aleksandra, "Using Sentiment Analysis of Twitter Data for Determining Popularity of City Locations" in ICT innovations 2016: cognitive functions and next generation ICT systems, 665 (2018):156-164, https://doi.org/10.1007/978-3-319-68855-8_15 . .