Towards user psychological profile
Proceedings of the VIII Brazilian Symposium on Human Factors in Computing Systems
Make new friends, but keep the old: recommending people on social networking sites
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Proceedings of the 29th ACM international conference on Design of communication
Proceedings of the 11th Brazilian Symposium on Human Factors in Computing Systems
SoS: um algoritmo para identificar pessoas homófilas em redes sociais com o uso da tradução cultural
Proceedings of the 11th Brazilian Symposium on Human Factors in Computing Systems
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We propose a three-step method to identify people in social networks sites (SNS) who are talking about the same topics, even though they may be from different cultural backgrounds. Our method uses a cultural knowledge base from the OMCS-Br project to normalize cultural differences and find common interest among users based on statements they make various topics in a SNS. We evaluated three initial phrases that were used to search for sentences in a large social network using the cultural translation; we found that 81% of the retrieved sentences were judged to be related to the initial phrases. Thus, we have evidence that cultural normalization can support finding people talking about the same topic in a SNS even when they have different ways of saying the same thing. We believe that these culturally translated similarities can be used in a recommender system to contribute to the formation of homophilous online communities.