 Solution

Use the uniform probability measure on the Boolean hypercube. In the Fourier-Walsh transform convention ${\chi }_S(x)=(-1{)}^{{\sum }_{i\in S}{x}_i}$, write $f={\sum }_S{\alpha }_S{\chi }_S$ with ${\alpha }_S=\mathbb{E}[f{\chi }_S]$. For the indicator $f$, Parseval's identity givesThe flip-probability influence satisfies ${\beta }_i=4{\sum }_{S\ni i}{\alpha }_S^2$, and summing gives ${\sum }_{S\ne \varnothing }|S|{\alpha }_S^2=\frac{1}{4}{\sum }_i{\beta }_i$.

For $p=1+\delta \in (1,2)$, Beckner's inequality says $\Vert T_{\sqrt{\delta }}g{\Vert }_2\le \Vert g{\Vert }_p$. Apply it to the discrete derivative of a Boolean function in coordinate $i$, viewed on the other $n-1$ coordinates. Its nonzero magnitude is $1/2$ and occurs with probability ${\beta }_i$, soSumming over $i$ gives the hypercontractive weighted influence bound