TY - JOUR
T1 - Knowledge-Based Sentiment Analysis and Visualization on Social Networks
AU - Vizcarra, Julio
AU - Kozaki, Kouji
AU - Torres Ruiz, Miguel
AU - Quintero, Rolando
N1 - Publisher Copyright:
© 2020, Ohmsha, Ltd. and Springer Japan KK, part of Springer Nature.
PY - 2021/4
Y1 - 2021/4
N2 - A knowledge-based methodology is proposed for sentiment analysis on social networks. The work was focused on semantic processing taking into account the content handling the public user’s opinions as excerpts of knowledge. Our approach implements knowledge graphs, similarity measures, graph theory algorithms, and a disambiguation process. The results obtained were compared with data retrieved from Twitter and users’ reviews in Amazon. We measured the efficiency of our contribution with precision, recall, and the F-measure, comparing it with the traditional method of looking up concepts in dictionaries which usually assign averages. Moreover, an analysis was carried out to find the best performance for the classification by using polarity, sentiment, and a polarity–sentiment hybrid. A study is presented for arguing the advantage of using a disambiguation process in knowledge processing. A visualization system presents the social graphs to display the sentiment information of each comment as well as the social structure and communications in the network.
AB - A knowledge-based methodology is proposed for sentiment analysis on social networks. The work was focused on semantic processing taking into account the content handling the public user’s opinions as excerpts of knowledge. Our approach implements knowledge graphs, similarity measures, graph theory algorithms, and a disambiguation process. The results obtained were compared with data retrieved from Twitter and users’ reviews in Amazon. We measured the efficiency of our contribution with precision, recall, and the F-measure, comparing it with the traditional method of looking up concepts in dictionaries which usually assign averages. Moreover, an analysis was carried out to find the best performance for the classification by using polarity, sentiment, and a polarity–sentiment hybrid. A study is presented for arguing the advantage of using a disambiguation process in knowledge processing. A visualization system presents the social graphs to display the sentiment information of each comment as well as the social structure and communications in the network.
KW - Conceptual similarity
KW - Disambiguation
KW - Knowledge engineering
KW - Knowledge graph
KW - Sentiment analysis
UR - http://www.scopus.com/inward/record.url?scp=85089974102&partnerID=8YFLogxK
U2 - 10.1007/s00354-020-00103-1
DO - 10.1007/s00354-020-00103-1
M3 - Artículo
AN - SCOPUS:85089974102
SN - 0288-3635
VL - 39
SP - 199
EP - 229
JO - New Generation Computing
JF - New Generation Computing
IS - 1
ER -