Half centuries of follow-up survey has enabled the architects and urban planners to design rationally by the aid of planning Nonetheless, limitation has occurred at planning because city has been changing its utility ...Half centuries of follow-up survey has enabled the architects and urban planners to design rationally by the aid of planning Nonetheless, limitation has occurred at planning because city has been changing its utility in accordance with its users＇ demand. In this paper, the authors proposed a method to analyze trait of users in market areas near stations by analyzing location based social network. After the datum collection from geotagged tweets, these GPS （global positioning system） datum were plotted to map attained from yahoo open location platform. Then the morphological analysis and terminology extraction system extracted the keywords and their scores. After calculating the distance from stations and users＇ GPS coordination, the authors extracted the array of keywords and corresponding scores in some station market area. Lastly, ratios of all users＇ scores and city＇s scores were calculated to examine the locality. Full combination of data collection, natural language processing and visualization enabled the authors to envisage distribution of collective background in city.展开更多
Location based social networks（ LBSNs） provide location specific data generated from smart phone into online social networks thus people can share their points of interest（ POIs）. POI collections are complex and c...Location based social networks（ LBSNs） provide location specific data generated from smart phone into online social networks thus people can share their points of interest（ POIs）. POI collections are complex and can be influenced by various factors,such as user preferences,social relationships and geographical influence. Therefore,recommending new locations in LBSNs requires to take all these factors into consideration. However,one problem is how to determine optimal weights of influencing factors in an algorithm in which these factors are combined. The user similarity can be obtained from the user check-in data,or from the user friend information,or based on the different geographical influences on each user＇s check-in activities. In this paper,we propose an algorithm that calculates the user similarity based on check-in records and social relationships,using a proposed weighting function to adjust the weights of these two kinds of similarities based on the geographical distance between users. In addition,a non-parametric density estimation method is applied to predict the unique geographical influence on each user by getting the density probability plot of the distance between every pair of user＇s check-in locations. Experimental results,using foursquare datasets,have shown that comparisons between the proposed algorithm and the other five baseline recommendation algorithms in LBSNs demonstrate that our proposed algorithm is superior in accuracy and recall,furthermore solving the sparsity problem.展开更多
Introduction:To evaluate the efficiency and effectiveness of Volunteer-Based Social Network human immunodeficiency virus(HIV)Testing Services(VBSNS).Methods:Collaborating with a local nongovernmental organization,we r...Introduction:To evaluate the efficiency and effectiveness of Volunteer-Based Social Network human immunodeficiency virus(HIV)Testing Services(VBSNS).Methods:Collaborating with a local nongovernmental organization,we recruited eligible elderly men who have sex with men(MSM)between 2021 and 2024.Participants were assigned to either the traditional Community-Based HIV Testing Services(CBHTS)group or the VBSNS group.We conducted questionnaire surveys,HIV and syphilis antibody rapid testing.Results:We recruited 144 volunteers,each of whom facilitated HIV testing for 9.13 participants on average.VBSNS accounted for 47.9%of all HIV tests and covered 66.6%of suburban areas.It also accounted for 67.2%of all newly reported cases,compared to only 32.8%for CBHTS.A higher proportion of testers who were under age 60,single,married,or cohabiting,with an education level of below junior college participated in VBSNS.Conversely,a smaller proportion of VBSNS participants reported identifying as homosexual,practiced HIV prevention measures beyond condom use,and had received HIV testing.Conclusions:VBSNS effectively increased HIV testing uptake and new case identification among MSM in remote areas,successfully reaching a high-risk population.This model provides a valuable alternative for settings where traditional methods such as on-site testing and counseling are inaccessible.展开更多
文摘Half centuries of follow-up survey has enabled the architects and urban planners to design rationally by the aid of planning Nonetheless, limitation has occurred at planning because city has been changing its utility in accordance with its users＇ demand. In this paper, the authors proposed a method to analyze trait of users in market areas near stations by analyzing location based social network. After the datum collection from geotagged tweets, these GPS （global positioning system） datum were plotted to map attained from yahoo open location platform. Then the morphological analysis and terminology extraction system extracted the keywords and their scores. After calculating the distance from stations and users＇ GPS coordination, the authors extracted the array of keywords and corresponding scores in some station market area. Lastly, ratios of all users＇ scores and city＇s scores were calculated to examine the locality. Full combination of data collection, natural language processing and visualization enabled the authors to envisage distribution of collective background in city.
文摘Location based social networks（ LBSNs） provide location specific data generated from smart phone into online social networks thus people can share their points of interest（ POIs）. POI collections are complex and can be influenced by various factors,such as user preferences,social relationships and geographical influence. Therefore,recommending new locations in LBSNs requires to take all these factors into consideration. However,one problem is how to determine optimal weights of influencing factors in an algorithm in which these factors are combined. The user similarity can be obtained from the user check-in data,or from the user friend information,or based on the different geographical influences on each user＇s check-in activities. In this paper,we propose an algorithm that calculates the user similarity based on check-in records and social relationships,using a proposed weighting function to adjust the weights of these two kinds of similarities based on the geographical distance between users. In addition,a non-parametric density estimation method is applied to predict the unique geographical influence on each user by getting the density probability plot of the distance between every pair of user＇s check-in locations. Experimental results,using foursquare datasets,have shown that comparisons between the proposed algorithm and the other five baseline recommendation algorithms in LBSNs demonstrate that our proposed algorithm is superior in accuracy and recall,furthermore solving the sparsity problem.
基金Supported by the National Natural Science Foundation of China(Grant No.72374153)Tianjin Health Research Project(Grant No.TJWJ2023QN092)Public Health Professionals Promotion Project.
文摘Introduction:To evaluate the efficiency and effectiveness of Volunteer-Based Social Network human immunodeficiency virus(HIV)Testing Services(VBSNS).Methods:Collaborating with a local nongovernmental organization,we recruited eligible elderly men who have sex with men(MSM)between 2021 and 2024.Participants were assigned to either the traditional Community-Based HIV Testing Services(CBHTS)group or the VBSNS group.We conducted questionnaire surveys,HIV and syphilis antibody rapid testing.Results:We recruited 144 volunteers,each of whom facilitated HIV testing for 9.13 participants on average.VBSNS accounted for 47.9%of all HIV tests and covered 66.6%of suburban areas.It also accounted for 67.2%of all newly reported cases,compared to only 32.8%for CBHTS.A higher proportion of testers who were under age 60,single,married,or cohabiting,with an education level of below junior college participated in VBSNS.Conversely,a smaller proportion of VBSNS participants reported identifying as homosexual,practiced HIV prevention measures beyond condom use,and had received HIV testing.Conclusions:VBSNS effectively increased HIV testing uptake and new case identification among MSM in remote areas,successfully reaching a high-risk population.This model provides a valuable alternative for settings where traditional methods such as on-site testing and counseling are inaccessible.
