113457 - predicting the scale.pdf (469.53 kB)
Predicting the scale of trending topic diffusion among online communities
conference contribution
posted on 2023-05-23, 11:41 authored by Kim, D, Han, SC, Lee, S, Byeong KangByeong KangOnline trending topics represent the most popular topics among users in certain online community, such as a country community. Trending topics in one community are different from others since the users in the community may discuss different topics from other communities. Surprisingly, almost 90% of trending topics are diffused among multiple online communities, so it shows peoples interests in a certain community can be shared to others in another community. The aim of this research is to predict the scale of trending topic diffusion among different online communities. The scale of diffusion represents the number of online communities that a trending topic diffuses. We proposed a diffusion scale prediction model for trending topics with the following four features, including community innovation feature, context feature, topic feature, and rank feature. We examined the proposed model with four different machine learning in predicting the scale of diffusion in Twitter Trending Topics among 8 English-speaking countries. Our model achieved the highest prediction accuracy (80.80%) with C4.5 decision tree.
History
Publication title
Lecture Notes in Computer Science 8867: Proceedings of the 14th Pacific Rim Knowledge Acquisition Workshop - Knowledge Management & Acquisition for Intelligent Systems)Volume
9806Editors
H Ohwada & K YoshidaPagination
153-165ISSN
0302-9743Department/School
School of EngineeringPublisher
Springer International PublishingPlace of publication
SwitzerlandEvent title
14th Pacific Rim Knowledge Acquisition WorkshopEvent Venue
Phuket, ThailandDate of Event (Start Date)
2016-08-22Date of Event (End Date)
2016-08-23Rights statement
Copyright unknownRepository Status
- Open