The number of blogs and other forms of opinionated online content has increased dramatically in recent years.Many fields,including academia and national security,place an emphasis on automated political article orient...The number of blogs and other forms of opinionated online content has increased dramatically in recent years.Many fields,including academia and national security,place an emphasis on automated political article orientation detection.Political articles(especially in the Arab world)are different from other articles due to their subjectivity,in which the author’s beliefs and political affiliation might have a significant influence on a political article.With categories representing the main political ideologies,this problem may be thought of as a subset of the text categorization(classification).In general,the performance of machine learning models for text classification is sensitive to hyperparameter settings.Furthermore,the feature vector used to represent a document must capture,to some extent,the complex semantics of natural language.To this end,this paper presents an intelligent system to detect political Arabic article orientation that adapts the categorical boosting(CatBoost)method combined with a multi-level feature concept.Extracting features at multiple levels can enhance the model’s ability to discriminate between different classes or patterns.Each level may capture different aspects of the input data,contributing to a more comprehensive representation.CatBoost,a robust and efficient gradient-boosting algorithm,is utilized to effectively learn and predict the complex relationships between these features and the political orientation labels associated with the articles.A dataset of political Arabic texts collected from diverse sources,including postings and articles,is used to assess the suggested technique.Conservative,reform,and revolutionary are the three subcategories of these opinions.The results of this study demonstrate that compared to other frequently used machine learning models for text classification,the CatBoost method using multi-level features performs better with an accuracy of 98.14%.展开更多
Background:The accurate estimation of temporal patterns of influenza may help in utilizing hospital resources and guiding influenza surveillance.This paper proposes functional data analysis(FDA)to improve the predicti...Background:The accurate estimation of temporal patterns of influenza may help in utilizing hospital resources and guiding influenza surveillance.This paper proposes functional data analysis(FDA)to improve the prediction of temporal patterns of influenza.Methods:We illustrate FDA methods using the weekly Influenza-like Illness(ILI)activity level data from the U.S.We propose to use the Fourier basis function for transforming discrete weekly data to the smoothed functional ILI activities.Functional analysis of variance(FANOVA)is used to examine the regional differences in temporal patterns and the impact of state's political orientation.Results:The ILI activity has a very distinct peak at the beginning and end of the year.There are significant differences in average level of ILI activities among geographic regions.However,the temporal patterns in terms of the peak and flat time are quite consistent across regions.The geographic and temporal patterns of ILI activities also depend on the political make-up of states.The states affiliated with Republicans had higher ILI activities than those affiliated with Democrats across the whole year.The influence of political party affiliation on temporal pattern is quite different among geographic regions.Conclusions:Functional data analysis can help us to reveal the temporal variability in average ILI levels,rate of change in ILI levels,and the effect of geographical regions.Consideration should be given to wider application of FDA to generate more accurate estimates in public health and biomedical research.展开更多
The positioning of anti-monopoly law depends on its unique value,goal and function.From the beginning,anti-monopoly law has had a great political and economic mission,and can become a“super law”with a grand value go...The positioning of anti-monopoly law depends on its unique value,goal and function.From the beginning,anti-monopoly law has had a great political and economic mission,and can become a“super law”with a grand value goal and a powerful function in economic adjustment.The uniqueness of the Internet,in capital,technology and business models,easily allows Internet platforms to grow anarchically,and to have a high correlation with anti-monopoly concerns.Internet anti-monopoly policy should first expand its thinking and elevate its stance in macro value,and seek appropriate legal and economic technical paths.China’s Internet platform anti-monopoly policy cannot simply follow today’s international and superficial trend,which does not contribute to positive experience and may conceal various interests.Instead,China’s Internet platform anti-monopoly policy should actively follow,respect and serve the substantial development interests of China’s digital economy,operating in a timely fashion and at the right location,in ways that are opportune,moderate and modest.It should always be committed to the innovation and development of China’s Internet industry and to international competitiveness.Internet anti-monopoly policy should adhere to the rule of law,build a corresponding rule system,ensure objectivity,neutrality and rationality,and prevent irrationality and over-excitement.展开更多
文摘The number of blogs and other forms of opinionated online content has increased dramatically in recent years.Many fields,including academia and national security,place an emphasis on automated political article orientation detection.Political articles(especially in the Arab world)are different from other articles due to their subjectivity,in which the author’s beliefs and political affiliation might have a significant influence on a political article.With categories representing the main political ideologies,this problem may be thought of as a subset of the text categorization(classification).In general,the performance of machine learning models for text classification is sensitive to hyperparameter settings.Furthermore,the feature vector used to represent a document must capture,to some extent,the complex semantics of natural language.To this end,this paper presents an intelligent system to detect political Arabic article orientation that adapts the categorical boosting(CatBoost)method combined with a multi-level feature concept.Extracting features at multiple levels can enhance the model’s ability to discriminate between different classes or patterns.Each level may capture different aspects of the input data,contributing to a more comprehensive representation.CatBoost,a robust and efficient gradient-boosting algorithm,is utilized to effectively learn and predict the complex relationships between these features and the political orientation labels associated with the articles.A dataset of political Arabic texts collected from diverse sources,including postings and articles,is used to assess the suggested technique.Conservative,reform,and revolutionary are the three subcategories of these opinions.The results of this study demonstrate that compared to other frequently used machine learning models for text classification,the CatBoost method using multi-level features performs better with an accuracy of 98.14%.
基金Authors acknowledged the Canadian Institute for Health Research(CIHR)Children's Hospital Research Institute of Manitoba(CHRIM)Foundation+1 种基金Visual and Automated Disease Analytics(VADA)graduate training program of Natural Sciences and Engineering Research Council of Canada(NSERC)for providing the funding opportunities to conduct this research.
文摘Background:The accurate estimation of temporal patterns of influenza may help in utilizing hospital resources and guiding influenza surveillance.This paper proposes functional data analysis(FDA)to improve the prediction of temporal patterns of influenza.Methods:We illustrate FDA methods using the weekly Influenza-like Illness(ILI)activity level data from the U.S.We propose to use the Fourier basis function for transforming discrete weekly data to the smoothed functional ILI activities.Functional analysis of variance(FANOVA)is used to examine the regional differences in temporal patterns and the impact of state's political orientation.Results:The ILI activity has a very distinct peak at the beginning and end of the year.There are significant differences in average level of ILI activities among geographic regions.However,the temporal patterns in terms of the peak and flat time are quite consistent across regions.The geographic and temporal patterns of ILI activities also depend on the political make-up of states.The states affiliated with Republicans had higher ILI activities than those affiliated with Democrats across the whole year.The influence of political party affiliation on temporal pattern is quite different among geographic regions.Conclusions:Functional data analysis can help us to reveal the temporal variability in average ILI levels,rate of change in ILI levels,and the effect of geographical regions.Consideration should be given to wider application of FDA to generate more accurate estimates in public health and biomedical research.
基金This paper is a phased achievement of major projects of National Social Science Foundation“Research on Intellectual Property Governance System of Digital Cyberspace”(project number:19ZDA164).
文摘The positioning of anti-monopoly law depends on its unique value,goal and function.From the beginning,anti-monopoly law has had a great political and economic mission,and can become a“super law”with a grand value goal and a powerful function in economic adjustment.The uniqueness of the Internet,in capital,technology and business models,easily allows Internet platforms to grow anarchically,and to have a high correlation with anti-monopoly concerns.Internet anti-monopoly policy should first expand its thinking and elevate its stance in macro value,and seek appropriate legal and economic technical paths.China’s Internet platform anti-monopoly policy cannot simply follow today’s international and superficial trend,which does not contribute to positive experience and may conceal various interests.Instead,China’s Internet platform anti-monopoly policy should actively follow,respect and serve the substantial development interests of China’s digital economy,operating in a timely fashion and at the right location,in ways that are opportune,moderate and modest.It should always be committed to the innovation and development of China’s Internet industry and to international competitiveness.Internet anti-monopoly policy should adhere to the rule of law,build a corresponding rule system,ensure objectivity,neutrality and rationality,and prevent irrationality and over-excitement.