Matches in SemOpenAlex for { <https://semopenalex.org/work/W3189896396> ?p ?o ?g. }
Showing items 1 to 100 of
100
with 100 items per page.
- W3189896396 endingPage "107368" @default.
- W3189896396 startingPage "107368" @default.
- W3189896396 abstract "Memes are the thoughts, behaviors, or styles spread among people in the same cultural atmosphere, which keeps changing in semantics and emotion during the interaction with different individuals. With the rapid development of Internet technology, various network topics have emerged endlessly, making memes a cultural gene to interact and change during the propagation process frequently. In recent decades, several methods were proposed to simulate the extraction and tracing mechanism of the meme. Many dedicated evolutionary algorithms using meme theory were crafted to solve domain-specific complex problems more effectively. However, there are also some obvious shortcomings in the current research on meme prediction and discovery. Firstly, there is no central node for the propagation of meme in social networks, and the current research has not taken the meme propagation environment into account. Secondly, the existing models for meme prediction primarily use the dynamics model of virus spreading, which still lacks the study of modeling methods for meme spreading characteristics. In this paper, we present a scheme on decentralized blockchain theory, which is capable of discovering and predicting the transmission of the meme. A multi-agent theory is introduced to interpret the potential rules in a different agent and simulate the meme tracing in a decentralized environment. By comparing with widely used methods in the meme prediction experiment, the results demonstrate that the multi-agent model has the best prediction effect under three types of extracted features. We implement a prototype of Meme-chain and conducted experiments. The experimental results demonstrate that Meme-chain achieves excellent results on meme discovery and meme information transaction process with low latency and high accuracy. Actual case studies of the four types of meme discovery revealed that our proposed Meme-chain can be applied to actual social media data for meme discovery, with significant commercial value and research implications." @default.
- W3189896396 created "2021-08-16" @default.
- W3189896396 creator A5052071646 @default.
- W3189896396 creator A5061363420 @default.
- W3189896396 creator A5073869833 @default.
- W3189896396 creator A5075394107 @default.
- W3189896396 creator A5080251597 @default.
- W3189896396 date "2021-10-01" @default.
- W3189896396 modified "2023-10-16" @default.
- W3189896396 title "Blockchain and multi-agent system for meme discovery and prediction in social network" @default.
- W3189896396 cites W1780764807 @default.
- W3189896396 cites W2023026264 @default.
- W3189896396 cites W2023501869 @default.
- W3189896396 cites W2027963417 @default.
- W3189896396 cites W2031801005 @default.
- W3189896396 cites W2080528796 @default.
- W3189896396 cites W2086618430 @default.
- W3189896396 cites W2087780634 @default.
- W3189896396 cites W2107878631 @default.
- W3189896396 cites W2160643434 @default.
- W3189896396 cites W2744353112 @default.
- W3189896396 cites W2787180832 @default.
- W3189896396 cites W2804344463 @default.
- W3189896396 cites W2809843308 @default.
- W3189896396 cites W2895570089 @default.
- W3189896396 cites W2914297008 @default.
- W3189896396 cites W2914797198 @default.
- W3189896396 cites W2921150100 @default.
- W3189896396 cites W2922081827 @default.
- W3189896396 cites W2922401517 @default.
- W3189896396 cites W2966317260 @default.
- W3189896396 cites W2970196897 @default.
- W3189896396 cites W2981579759 @default.
- W3189896396 cites W2996527614 @default.
- W3189896396 cites W2996763051 @default.
- W3189896396 cites W2997035848 @default.
- W3189896396 cites W2997883686 @default.
- W3189896396 cites W3029391820 @default.
- W3189896396 cites W3034461381 @default.
- W3189896396 cites W3097475179 @default.
- W3189896396 cites W3099251797 @default.
- W3189896396 cites W3102744027 @default.
- W3189896396 cites W3109159314 @default.
- W3189896396 cites W3115710758 @default.
- W3189896396 cites W3117185436 @default.
- W3189896396 cites W3121887278 @default.
- W3189896396 cites W3123459983 @default.
- W3189896396 cites W3132084504 @default.
- W3189896396 cites W3169646931 @default.
- W3189896396 doi "https://doi.org/10.1016/j.knosys.2021.107368" @default.
- W3189896396 hasPublicationYear "2021" @default.
- W3189896396 type Work @default.
- W3189896396 sameAs 3189896396 @default.
- W3189896396 citedByCount "10" @default.
- W3189896396 countsByYear W31898963962022 @default.
- W3189896396 countsByYear W31898963962023 @default.
- W3189896396 crossrefType "journal-article" @default.
- W3189896396 hasAuthorship W3189896396A5052071646 @default.
- W3189896396 hasAuthorship W3189896396A5061363420 @default.
- W3189896396 hasAuthorship W3189896396A5073869833 @default.
- W3189896396 hasAuthorship W3189896396A5075394107 @default.
- W3189896396 hasAuthorship W3189896396A5080251597 @default.
- W3189896396 hasConcept C111919701 @default.
- W3189896396 hasConcept C119857082 @default.
- W3189896396 hasConcept C138673069 @default.
- W3189896396 hasConcept C154945302 @default.
- W3189896396 hasConcept C2522767166 @default.
- W3189896396 hasConcept C41008148 @default.
- W3189896396 hasConcept C98045186 @default.
- W3189896396 hasConceptScore W3189896396C111919701 @default.
- W3189896396 hasConceptScore W3189896396C119857082 @default.
- W3189896396 hasConceptScore W3189896396C138673069 @default.
- W3189896396 hasConceptScore W3189896396C154945302 @default.
- W3189896396 hasConceptScore W3189896396C2522767166 @default.
- W3189896396 hasConceptScore W3189896396C41008148 @default.
- W3189896396 hasConceptScore W3189896396C98045186 @default.
- W3189896396 hasFunder F4320320929 @default.
- W3189896396 hasFunder F4320322725 @default.
- W3189896396 hasFunder F4320335777 @default.
- W3189896396 hasFunder F4320335787 @default.
- W3189896396 hasLocation W31898963961 @default.
- W3189896396 hasOpenAccess W3189896396 @default.
- W3189896396 hasPrimaryLocation W31898963961 @default.
- W3189896396 hasRelatedWork W2961085424 @default.
- W3189896396 hasRelatedWork W3046775127 @default.
- W3189896396 hasRelatedWork W3107602296 @default.
- W3189896396 hasRelatedWork W3170094116 @default.
- W3189896396 hasRelatedWork W3209574120 @default.
- W3189896396 hasRelatedWork W4210805261 @default.
- W3189896396 hasRelatedWork W4306674287 @default.
- W3189896396 hasRelatedWork W4312192474 @default.
- W3189896396 hasRelatedWork W4386462264 @default.
- W3189896396 hasRelatedWork W4387297750 @default.
- W3189896396 hasVolume "229" @default.
- W3189896396 isParatext "false" @default.
- W3189896396 isRetracted "false" @default.
- W3189896396 magId "3189896396" @default.
- W3189896396 workType "article" @default.