A Graph Based Approach for Effective Influencer Marketing
We present a novel graph-based approach to find the optimal set of influencers from a large pool of influencers. The goal is to select minimum number of influencers that can reach the desired audience. In order to find such a set, one has to compute the reach of all possible combinations of available influencers resulting in complexity of order O (n^2 ). Our proposed greedy approach selects the pair of influencers that results in highest reach at every iteration reducing the complexity to O(2n). Our work is complimented with analysis of 550 Instagram influencers and over 100,000 post. After the analysis, we concluded that influencers who prefer quality over quantity receives better engagement. Influencers sharing 3 posts per week and posts with caption length of over 500 characters relatively received better engagement number.
Authors: Salman Ansari, Muhammad Ahsan Tahir
Publication: International Journal of Data Mining & Knowledge Management Process (IJDKP) Vol.9, No.4, July 2019
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