As a new form of social e-commerce, live streaming e-commerce is becoming increasingly popular among Chinese consumers. Live streaming brings huge opportunities, and we can take measures to further expand the dissemination of live streaming information. A live streaming information dissemination game model based on social evolutionary game theory is presented to simulate multiple complex live streaming e-commerce networks. The introduction of incentive mechanism in the model further quantifies the internal relation between rewards and live streaming information dissemination to a certain extent and predicts the ratings of live streaming in networks with different update frequency of social relationships. The simulation results indicate that the reputation environment in social networks, adjusting frequency of relationship, pre-broadcast rewards to post-broadcast rewards ratio all have certain ranges of impact on information dissemination in live streaming e-commerce environment and then affect the live streaming ratings. These findings offer insights into the dissemination of live streaming information in social networks.
Space is the most fundamental organizing dimension for information that forms the basic spatial understanding around which all other temporal and semantic details are situated. Various types of web information are present in our daily lives, and spatial content can facilitate the understanding of that information. Hence, many studies have been conducted to extract the implicit spatial location from different web resources, and they have mainly investigated web textual information. However, the existing studies mainly focus on the extraction or simple presentation of the location of the information, while further exploration and visualization of the information through the comprehensive consideration of its spatial, temporal, and semantic dimensions have rarely been performed. Thus, this paper proposes a novel modeling and visualization framework for location-referenced web textual information. The framework applies an information model to structurally extract and resolve spatial content along with the temporal and semantic elements from the location-referenced information items. Based on the constructed information model, the information items are hierarchically clustered and visualized by combining map mashups with cartographic processes and methods. This framework enables users to interactively index and browses individual information items. Furthermore, the association relationships involved in the information set are explored in our work. With knowledge graphs that are automatically generated based on the information model, a high-level understanding of the information set can be obtained by users.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.