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Besides the arbitrary estimation, we also employed another method – calibration with the help of logistic function, to forecast Douyin’s user growth in the future. As shown in Figure 15, Douyin exhibits strong historical growth. To better understand the company’s potential growth, we extended the methodology proposed in prior research by Cauwels and Sornette here to Douyin and incorporated the concept of discrete growth rate. We plotted Douyin’s discrete growth rate against its MAU over time to see the fit of data as well as to obtain values of initial growth rate r, and its maximum carrying capacity K. 120% 100% 80% 60% 40% 20% 0% -20% y = -6.44E-04x + 3.26E-01 R2 = 1.30E-01 y = -1.08E-03x + 4.72E-01 R2 = 3.02E-01 0 50 100 150 200 250 300 350 400 450 500 MAU [mn] Figure 16: Discrete growth rate as a linear function of Douyin’s MAU Note: 1) Blue series covers data from Feburary 2017 to January 2019, blue dots represent data points over time whearas the dotted line depicts the discrete growth rate as a linear function of Douyin’s MAU – 𝑦 = −6.44𝐸 − 04𝑥 + 3.26𝐸 − 01 with an R-square of 0.13. This gives us 𝑎 = −6.44 ∗ 10−4 and 𝑏 = 3.26 ∗ 10−1. 2) Orange series covers data from Feburary 2018 to January 2019 – data from year 2017 was excluded here as it was the period of extreme user growth. Exclusion of such data might smooth the data and offer a better fit thus a more reasonable predictions into the future. Orange dots represent data points over time whearas the dotted line depicts the discrete growth rate as a linear function of Douyin’s MAU – 𝑦 = −1.08𝐸 − 03𝑥 + 4.72𝐸 − 01 with an R-square of 0.30. This gives us 𝑎 = −1.08 ∗ 10−3 and 𝑏 = 4.72 ∗ 10−1. - 44 - Discrete Growth RatePDF Image | Analysis of ByteDance with a close look on Douyin TikTok
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