Currently, with the rapid growth of online media, more people are obtaining information from it. However, traditional hotspot mining algorithms cannot achieve precise and fast control of hot topics. Aiming at the problem of poor accuracy and timeliness in current news media hotspot mining methods, this paper proposes a hotspot mining method based on the co-occurrence word model. First, a new co-occurrence word model based on word weight is proposed. Then, for key phrase extraction, a hotspot mining algorithm based on the co-occurrence word model and improved smooth inverse frequency rank (SIFRANK) is designed. Finally, the Spark computing framework is introduced to improve the computing efficiency. The experimental outcomes expresses that the new word discovery algorithm discovered 16871 and 17921 new words in the Weibo Short News and Weibo Short Text datasets respectively. The heat weight values of the keywords obtained by the improved SIFRANK reaches 0.9356, 0.9991, and 0.6117. In the Covid19 Tweets dataset, the accuracy is 0.6223, the recall is 0.7015, and the F1 value is 0.6605. In the President-elects Tweets dataset, the accuracy is 0.6418, the recall is 0.7162, and the F1 value is 0.6767. After applying the Spark computing framework, the running speed has significantly improved. The text mining news media hotspot mining method based on the co-occurrence word model proposed in this study has improved the accuracy and efficiency of mining hot topics, and has great practical significance.
Citation: Xinyun Zhang, Tao Ding. Co-occurrence word model for news media hotspot mining-text mining method design[J]. Mathematical Biosciences and Engineering, 2024, 21(4): 5411-5429. doi: 10.3934/mbe.2024238
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Currently, with the rapid growth of online media, more people are obtaining information from it. However, traditional hotspot mining algorithms cannot achieve precise and fast control of hot topics. Aiming at the problem of poor accuracy and timeliness in current news media hotspot mining methods, this paper proposes a hotspot mining method based on the co-occurrence word model. First, a new co-occurrence word model based on word weight is proposed. Then, for key phrase extraction, a hotspot mining algorithm based on the co-occurrence word model and improved smooth inverse frequency rank (SIFRANK) is designed. Finally, the Spark computing framework is introduced to improve the computing efficiency. The experimental outcomes expresses that the new word discovery algorithm discovered 16871 and 17921 new words in the Weibo Short News and Weibo Short Text datasets respectively. The heat weight values of the keywords obtained by the improved SIFRANK reaches 0.9356, 0.9991, and 0.6117. In the Covid19 Tweets dataset, the accuracy is 0.6223, the recall is 0.7015, and the F1 value is 0.6605. In the President-elects Tweets dataset, the accuracy is 0.6418, the recall is 0.7162, and the F1 value is 0.6767. After applying the Spark computing framework, the running speed has significantly improved. The text mining news media hotspot mining method based on the co-occurrence word model proposed in this study has improved the accuracy and efficiency of mining hot topics, and has great practical significance.
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63. | Yan Chen, Haitao Song, Shengqiang Liu, Evaluations of COVID-19 epidemic models with multiple susceptible compartments using exponential and non-exponential distribution for disease stages, 2022, 7, 24680427, 795, 10.1016/j.idm.2022.11.004 | |
64. | Luis Almeida, Pierre-Alexandre Bliman, Grégoire Nadin, Benoît Perthame, Nicolas Vauchelet, Final size and convergence rate for an epidemic in heterogeneous populations, 2021, 31, 0218-2025, 1021, 10.1142/S0218202521500251 | |
65. | Jaafar El Karkri, Mohammed Benmir, 2022, 9780323905046, 137, 10.1016/B978-0-32-390504-6.00014-0 | |
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71. | Florin Avram, Rim Adenane, Andrei Halanay, New Results and Open Questions for SIR-PH Epidemic Models with Linear Birth Rate, Loss of Immunity, Vaccination, and Disease and Vaccination Fatalities, 2022, 14, 2073-8994, 995, 10.3390/sym14050995 | |
72. | Jummy F. David, Sarafa A. Iyaniwura, Effect of Human Mobility on the Spatial Spread of Airborne Diseases: An Epidemic Model with Indirect Transmission, 2022, 84, 0092-8240, 10.1007/s11538-022-01020-8 | |
73. | Julien Arino, Pierre-Yves Boëlle, Evan Milliken, Stéphanie Portet, Risk of COVID-19 variant importation – How useful are travel control measures?, 2021, 6, 24680427, 875, 10.1016/j.idm.2021.06.006 | |
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75. | Florin Avram, Rim Adenane, Lasko Basnarkov, Gianluca Bianchin, Dan Goreac, Andrei Halanay, An Age of Infection Kernel, an R Formula, and Further Results for Arino–Brauer A, B Matrix Epidemic Models with Varying Populations, Waning Immunity, and Disease and Vaccination Fatalities, 2023, 11, 2227-7390, 1307, 10.3390/math11061307 | |
76. | Bolarinwa Bolaji, B. I. Omede, U. B. Odionyenma, P. B. Ojih, Abdullahi A. Ibrahim, Modelling the transmission dynamics of Omicron variant of COVID-19 in densely populated city of Lagos in Nigeria, 2023, 2714-4704, 1055, 10.46481/jnsps.2023.1055 | |
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78. | Sarita Bugalia, Jai Prakash Tripathi, Assessing potential insights of an imperfect testing strategy: Parameter estimation and practical identifiability using early COVID-19 data in India, 2023, 10075704, 107280, 10.1016/j.cnsns.2023.107280 | |
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83. | Preeti Deolia, Anuraj Singh, Analysing the probable insights of ADE in dengue vaccination embodying sequential Zika infection and waning immunity, 2024, 139, 2190-5444, 10.1140/epjp/s13360-023-04813-5 | |
84. | Donald S. Burke, Origins of the problematic E in SEIR epidemic models, 2024, 24680427, 10.1016/j.idm.2024.03.003 | |
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86. | Qian Li, Biao Tang, Yanni Xiao, Multiple epidemic waves in a switching system with multi-thresholds triggered alternate control, 2024, 112, 0924-090X, 8721, 10.1007/s11071-024-09533-8 | |
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88. | Francesca Calà Campana, Rami Katz, Giulia Giordano, Sequential-Quadratic-Hamiltonian Optimal Control of Epidemic Models With an Arbitrary Number of Infected and Non-Infected Compartments, 2024, 8, 2475-1456, 1805, 10.1109/LCSYS.2024.3412775 | |
89. | Komal Tanwar, Nitesh Kumawat, Jai Prakash Tripathi, Sudipa Chauhan, Anuj Mubayi, Evaluating vaccination timing, hesitancy and effectiveness to prevent future outbreaks: insights from COVID-19 modelling and transmission dynamics, 2024, 11, 2054-5703, 10.1098/rsos.240833 | |
90. | Justin K. Sheen, Lee Kennedy-Shaffer, Michael Z. Levy, Charlotte Jessica E. Metcalf, Claudio José Struchiner, Design of field trials for the evaluation of transmissible vaccines in animal populations, 2025, 21, 1553-7358, e1012779, 10.1371/journal.pcbi.1012779 | |
91. | Rim Adenane, Mohamed El Fatini, 2024, Actuarial Risks Associated to Disease Outbreaks and Insurance Plans Under Media Coverage Strategy, 979-8-3503-8735-3, 1, 10.1109/ICOA62581.2024.10754019 |