As social media and online activity continue to pervade all age groups, it serves as a crucial platform for sharing personal experiences and opinions as well as information about attitudes and preferences for certain ...As social media and online activity continue to pervade all age groups, it serves as a crucial platform for sharing personal experiences and opinions as well as information about attitudes and preferences for certain interests or purchases. This generates a wealth of behavioral data, which, while invaluable to businesses, researchers, policymakers, and the cybersecurity sector, presents significant challenges due to its unstructured nature. Existing tools for analyzing this data often lack the capability to effectively retrieve and process it comprehensively. This paper addresses the need for an advanced analytical tool that ethically and legally collects and analyzes social media data and online activity logs, constructing detailed and structured user profiles. It reviews current solutions, highlights their limitations, and introduces a new approach, the Advanced Social Analyzer (ASAN), that bridges these gaps. The proposed solutions technical aspects, implementation, and evaluation are discussed, with results compared to existing methodologies. The paper concludes by suggesting future research directions to further enhance the utility and effectiveness of social media data analysis.展开更多
Human activities on street spaces are affected by both physical and non-physical settings on streets.These two aspects are primarily impacted by land use which results in the uneven distribution of different activitie...Human activities on street spaces are affected by both physical and non-physical settings on streets.These two aspects are primarily impacted by land use which results in the uneven distribution of different activities on streets.This research investigates land use patterns and their characteristics in association to user’s behaviors.By using mixed qualitative and quantitative research methods,e.g.,place-centered behavioral map,observation,visual encounter surveys,machine learning,the relationship between user’s behavior and land use characteristics along the street is unveiled.All user behaviors along both types of streets were classified into six main categories,with 26 subcategories.The observation results show that the residential use of land along the street was transformed into the commercial use for various types of shophouses based on the resident’s ideas.There is a great correlation between land use and user’s activities.These findings give support to authorities to manage urban streets and develop a sustainable policy for improving street spaces.Further,this research contributes useful information to urban designers and planners in creating a successful street space that is appropriate for the Vietnam Community.展开更多
文摘As social media and online activity continue to pervade all age groups, it serves as a crucial platform for sharing personal experiences and opinions as well as information about attitudes and preferences for certain interests or purchases. This generates a wealth of behavioral data, which, while invaluable to businesses, researchers, policymakers, and the cybersecurity sector, presents significant challenges due to its unstructured nature. Existing tools for analyzing this data often lack the capability to effectively retrieve and process it comprehensively. This paper addresses the need for an advanced analytical tool that ethically and legally collects and analyzes social media data and online activity logs, constructing detailed and structured user profiles. It reviews current solutions, highlights their limitations, and introduces a new approach, the Advanced Social Analyzer (ASAN), that bridges these gaps. The proposed solutions technical aspects, implementation, and evaluation are discussed, with results compared to existing methodologies. The paper concludes by suggesting future research directions to further enhance the utility and effectiveness of social media data analysis.
文摘Human activities on street spaces are affected by both physical and non-physical settings on streets.These two aspects are primarily impacted by land use which results in the uneven distribution of different activities on streets.This research investigates land use patterns and their characteristics in association to user’s behaviors.By using mixed qualitative and quantitative research methods,e.g.,place-centered behavioral map,observation,visual encounter surveys,machine learning,the relationship between user’s behavior and land use characteristics along the street is unveiled.All user behaviors along both types of streets were classified into six main categories,with 26 subcategories.The observation results show that the residential use of land along the street was transformed into the commercial use for various types of shophouses based on the resident’s ideas.There is a great correlation between land use and user’s activities.These findings give support to authorities to manage urban streets and develop a sustainable policy for improving street spaces.Further,this research contributes useful information to urban designers and planners in creating a successful street space that is appropriate for the Vietnam Community.
