TY  - JOUR
T1  - Geovisualization Way for Exploiting Customer’s Emotions on Twitter
AU - Ma`ady, Mochamad Nizar Palefi AU - Djunaidy, Arif AU - Kusumawardani, Renny Pradina 
JO  - Journal of Engineering and Applied Sciences
VL  - 14
IS  - 4
SP  - 1182
EP  - 1188
PY  - 2019
DA  - 2001/08/19
SN  - 1816-949x
DO  - jeasci.2019.1182.1188
UR  - https://makhillpublications.co/view-article.php?doi=jeasci.2019.1182.1188
KW  - Twitter
KW  -emotions
KW  -Naive Bayes
KW  -heat map
KW  -classification
KW  -opinion
AB  - Tight competition among companies has been making many companies to increase their efforts to
collect information for the sake of their service analysis. Recorded data in Twitter can be used as a potential
data which is becoming one of the most popular social media in the world. Naive Bayes is developed to observe
positive and negative opinions of the customers on the services given by the company in the form of heat map.
Data pre-processing was performed in order to determine attributes to choose data accompanying with their
associated coordinates and to decide which words are considered as positive or negative opinion. Heat map
was used to visualize density level gradation of opinions. The use of heat map is capable to observe customer’s
opinions density level based on their colour gradation visualization that are presented in certain radius from
one coordinate observing point specified by the user.
ER  -