ACADSTAFF UGM
| Title | : | An Extended Approach of Weight Collective Influence Graph for Detection Influence Actor |
| Author | : |
GALIH HENDRO MARTONO (1) Dr. Azhari, MT. (2) Dr. techn. Khabib Mustofa, S.Si., M.Kom. (3) |
| Date | : | 31 2022 |
| Keyword | : | Collective Influence,Centrality measure,hate speech,influence actor,Bahasa,weighted collective influence Collective Influence,Centrality measure,hate speech,influence actor,Bahasa,weighted collective influence |
| Abstract | : | Over the last decade, numerous methods have been developed to detect the influential actors of hate speech in social networks, one of which is the Collective Influence (CI) method. However, this method is associated with unweighted datasets, which makes it inappropriate for social media, significantly using weight datasets. Furthermore, the datasets are available in English. This study proposes a new CI method called the Weighted Collective Influence Graph (WCIG), which uses the weights and neighbour values to detect the influence of hate speech. A total of 49, 992 Indonesian tweets were and extracted from Indonesian Twitter accounts, from January 01 to January 22, 2021. The data collected are also used to compare the results of the proposed WCIG method to determine the influential actors in the dissemination of information. The experiment was carried out four times using different ∂ parameters, namely 2, 4, 8 and 16. The results showed that the usernames _bernacleboy and zack_rockstar are influential actors in the dataset. Furthermore, the time needed to process WCIG calculations on HPC is 34-75 hours because the larger the parameter used, the greater the processing time. |
| Group of Knowledge | : | Ilmu Komputer |
| Original Language | : | English |
| Level | : | Internasional |
| Status | : |
Published
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