Popularity of personalities in society as driven by news
Abstract
We extract names of individuals in a yearlong archive of articles of a major Philippine daily in English for the year 2010. Aggregated and per-section data reveal stable Zipf’s law distributions when name rank R is plotted with frequency, f(R) ∠R−β, with scaling exponent β ≈ 0.60, which indicates a less steep plot compared to that of common (i.e. non-name) dictionary words. This shows that a highly dynamic system such as the society obeys a scale-free power law distribution. Also, the lifetime of high-ranked individuals is tracked, revealing a ‘time constant’ for decay lifetime of names particularly after the elections. Aside from real-time quantitative characterization of society, trends manifested by the name statistics in news may provide a framework in predicting possi- ble “extreme events†in society, like violent upheavals and mass movements.
Downloads
Published
Issue
Section
License
By submitting their manuscript to the Samahang Pisika ng Pilipinas (SPP) for consideration, the Authors warrant that their work is original, does not infringe on existing copyrights, and is not under active consideration for publication elsewhere.
Upon acceptance of their manuscript, the Authors further agree to grant SPP the non-exclusive, worldwide, and royalty-free rights to record, edit, copy, reproduce, publish, distribute, and use all or part of the manuscript for any purpose, in any media now existing or developed in the future, either individually or as part of a collection.
All other associated economic and moral rights as granted by the Intellectual Property Code of the Philippines are maintained by the Authors.
