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Time-focused analysis of connectivity and popularity of historical persons in Wikipedia., , and . Int. J. Digit. Libr., 20 (4): 287-305 (2019)Is your digital neighbor a reliable investment advisor?, , , , , and . WWW, page 3581-3591. ACM, (2023)User Participation in Cryptocurrency Derivative Markets., , , , and . AFT, volume 282 of LIPIcs, page 8:1-8:24. Schloss Dagstuhl - Leibniz-Zentrum für Informatik, (2023)Unfriend or ignore tweets?: A time series analysis on Japanese Twitter users suffering from information overload., , and . Comput. Hum. Behav., (2016)How Social Network Site Users' Motives Predict Their Online Network Sizes: A Quantile Regression Approach to Japanese Twitter Usage., , and . Int. J. Hum. Comput. Interaction, 35 (7): 548-558 (2019)The anatomy of tweet overload: How number of tweets received, number of friends, and egocentric network density affect perceived information overload., , and . Telematics Informatics, 32 (4): 853-861 (2015)Digital History Meets Wikipedia: Analyzing Historical Persons in Wikipedia., , and . JCDL, page 17-26. ACM, (2016)Parallelizing Local Search for CNF Satisfiability Using Vectorization and PVM., , , , and . ACM Journal of Experimental Algorithmics, (2002)Predicting Importance of Historical Persons using Wikipedia., , and . CIKM, page 1909-1912. ACM, (2016)Parallelizing Local Search for CNF Satisfiability Using Vectorization and PVM., , , , and . WAE, volume 1982 of Lecture Notes in Computer Science, page 123-134. Springer, (2000)