Abstract
We have developed a system for identifying the person who posted posts of interest. It calculates the similarity between the posts of interest and the résumé of each candidate person and then identifies the résumé with the highest similarity as that of the posting person. Identification accuracy was improved by using the posts of persons other than the target person. Evaluation using 30 student volunteers who permitted the use of their résumés and sets of tweets showed that using information from tweets of other persons dramatically improved identification accuracy. Identification accuracy was 0.36 and 0.53 when the number of other persons was 4 and 9, respectively. Those that the target person can be limited in 10 % of the candidates were 0.72 both with 4 and 9 such employees.
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Notes
- 1.
UEC is near Chofu station on the Keio line in Tokyo.
- 2.
The employer may know which of several employees owns which accounts. However, we can formulate an n–n matching problem by eliminating the known pairs.
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This work was supported by ISPS KAKENHI Grant Number 26330153.
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Ogawa, Y., Hashimoto, E., Ichino, M., Echizen, I., Yoshiura, H. (2015). De-anonymising Social Network Posts by Linking with Résumé. In: Abramowicz, W. (eds) Business Information Systems Workshops. BIS 2015. Lecture Notes in Business Information Processing, vol 228. Springer, Cham. https://doi.org/10.1007/978-3-319-26762-3_22
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