article
This paper presents a new information diffusion model that studies the impact of trendy topics on the diffusion process based on content analysis. The suggested model (<Formula format="inline"><TexMath><?TeX $SI_{t_w}R$?></TexMath><AltText>Math 1</AltText><File name="icsie2023-7-inline1" type="svg"/></Formula>) extends the SIR model by adding the topic weight (tw) that mirrors the topic significance reflected on the infection rate. In which, the new infection rate (λtw ) will be calculated by multiplying the normal infection rate (λ) with the topic weight (tw). An experimental study has been conducted on trendy and non-trendy topics and the results are compared to the classical SIR model. The simulation results of the <Formula format="inline"><TexMath><?TeX $SI_{t_w}R$?></TexMath><AltText>Math 2</AltText><File name="icsie2023-7-inline2" type="svg"/></Formula> model using Mathematica show the early diffusion of the trendy topics. It has been concluded that the number of infected accounts will accelerate within a shorter time due to the impact of the trendy topics. Therefore, the proposed model (<Formula format="inline"><TexMath><?TeX $SI_{t_w}R$?></TexMath><AltText>Math 3</AltText><File name="icsie2023-7-inline3" type="svg"/></Formula>) better reflects the diffusion process in the presence of trendy topics.
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DOI: 10.1145/3634848.3634855
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