Abstract
Finding important users from social media is a challenging and significant task. In this paper, we focus on the users in the blogosphere and propose an approach to identify prophetic bloggers by estimating bloggers’ prediction ability on buzzwords and categories. We conduct a time-series analysis on large-scale blog data, which includes categorizing a blogger into knowledgeable categories, identifying past buzzwords, analyzing a buzzword’s peak time content and growth period, and estimating a blogger’s prediction ability on a buzzword and on a category. Bloggers’ prediction ability on a buzzword is evaluated considering three factors: post earliness, content similarity and entry frequency. Bloggers’ prediction ability on a category is evaluated considering the buzzword coverage in that category. For calculating bloggers’ prediction ability on a category, we propose multiple formulas and compare the accuracy through experiments. Experimental results show that the proposed approach can find prophetic bloggers on real-world blog data.
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Notes
- 1.
Abenomics refers to the economic policies advocated by Shinzo Abe, the Prime Minister of Japan.
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This work was partially supported by JSPS KAKENHI Grant Number #26330351.
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Zhang, J., Inagaki, Y., Nakamoto, R., Nakajima, S. (2020). Identifying Prophetic Bloggers Based on Prediction Ability of Buzzwords and Categories. In: Ao, SI., Kim, H., Castillo, O., Chan, As., Katagiri, H. (eds) Transactions on Engineering Technologies. IMECS 2018. Springer, Singapore. https://doi.org/10.1007/978-981-32-9808-8_6
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