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 network
Source:
ICT innovations 2016: cognitive functions and next generation ICT systems, 2018, 665, 156-164
TY - CONF
AU - Dinkić, Nikola
AU - Džaković, Nikola
AU - Joković, Jugoslav
AU - Stoimenov, L.
AU - Đukić, Aleksandra
PY - 2018
UR - http://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",
url = "http://raf.arh.bg.ac.rs/handle/123456789/298",
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.
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. ICT innovations 2016: cognitive functions and next generation ICT systems. 2018;665:156-164
Dinkić Nikola, Džaković Nikola, Joković Jugoslav, Stoimenov L., Đukić Aleksandra, "Using Sentiment Analysis of Twitter Data for Determining Popularity of City Locations" 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 .
