Background Over the last few years,the rapid advancement of technology has led to the development of many approaches to digitalization.In this respect,metaverse provides 3D persistent virtual environments that can be ...Background Over the last few years,the rapid advancement of technology has led to the development of many approaches to digitalization.In this respect,metaverse provides 3D persistent virtual environments that can be used to access digital content,meet virtually,and perform several professional and leisure tasks.Among the numerous technologies supporting the metaverse,immersive Virtual Reality(VR)plays a primary role and offers highly interactive social experiences.Despite growing interest in this area,there are no clear design guidelines for creating environments tailored to the metaverse.Methods This study seeks to advance research in this area by moving from state-of-the-art studies on the design of immersive virtual environments in the context of metaverse and proposing how to integrate cutting-edge technologies within this context.Specifically,the best practices were identified by i)analyzing literature studies focused on human behavior in immersive virtual environments,ii)extracting common features of existing social VR platforms,and iii)conducting interviews with experts in a specific application domain.Specifically,this study considered the creation of a new virtual environment for MetaLibrary,a VR-based social platform aimed at integrating public libraries into metaverse.Several implementation challenges and additional requirements have been identified for the development of virtual environments(VEs).These elements were considered in the selection of specific cutting-edge technologies and their integration into the development process.A user study was also conducted to investigate some design aspects(namely lighting conditions and richness of the scene layout)for which deriving clear indications from the above analysis was not possible because different alternative configurations could be chosen.Results The work reported in this paper seeks to bridge the gap between existing VR platforms and related literature in the field,on the one hand,and requirements regarding immersive virtual environments for the metaverse,on the other hand,by reporting a set of best practices which were used to build a social virtual environment that meets users'expectations and needs.Conclusions Results suggest that carefully designed virtual environments can positively affect user experience and interaction within metaverse.The insights gained from this study offer valuable cues for developing immersive virtual environments for the metaverse to deliver more effective and engaging experiences.展开更多
Thalassemia syndrome is a genetic blood disorder induced by the reduction of normal hemoglobin production,resulting in a drop in the size of red blood cells.In severe forms,it can lead to death.This genetic disorder h...Thalassemia syndrome is a genetic blood disorder induced by the reduction of normal hemoglobin production,resulting in a drop in the size of red blood cells.In severe forms,it can lead to death.This genetic disorder has posed a major burden on public health wherein patients with severe thalassemia need periodic therapy of iron chelation and blood transfusion for survival.Therefore,controlling thalassemia is extremely important and is made by promoting screening to the general population,particularly among thalassemia carriers.Today Twitter is one of the most influential social media platforms for sharing opinions and discussing different topics like people’s health conditions and major public health affairs.Exploring individuals’sentiments in these tweets helps the research centers to formulate strategies to promote thalassemia screening to the public.An effective Lexiconbased approach has been introduced in this study by highlighting a classifier called valence aware dictionary for sentiment reasoning(VADER).In this study applied twitter intelligence tool(TWINT),Natural Language Toolkit(NLTK),and VADER constitute the three main tools.VADER represents a gold-standard sentiment lexicon,which is basically tailored to attitudes that are communicated by using social media.The contribution of this study is to introduce an effective Lexicon-based approach by highlighting a classifier calledVADERto analyze the sentiment of the general population,particularly among thalassemia carriers on the social media platform Twitter.In this study,the results showed that the proposed approach achieved 0.829,0.816,and 0.818 regarding precision,recall,together with F-score,respectively.The tweets were crawled using the search keywords,“thalassemia screening,”thalassemia test,“and thalassemia diagnosis”.Finally,results showed that India and Pakistan ranked the highest in mentions in tweets by the public’s conversations on thalassemia screening with 181 and 164 tweets,respectively.展开更多
This study examines the impact of communication on investors’trading frequency based on a unique dataset drawn from a Chinese social trading platform.We find robust evidence that real-account portfolio owners on the ...This study examines the impact of communication on investors’trading frequency based on a unique dataset drawn from a Chinese social trading platform.We find robust evidence that real-account portfolio owners on the platform trade more frequently under the influence of the comments posted by their leaders(the owners of portfolios they have followed).Moreover,portfolio owners are more sensitive to the quantity than to the tone of leaders’comments.Finally,both trading frequency and leaders’comments negatively impact portfolio owners’future performance.Our find-ings support the notion that social interaction promotes active investment strategies.展开更多
The cyber development of government service platform is just to integrate all the superiorities of the government to strengthen its roles such as service,performance and function to drive the social development active...The cyber development of government service platform is just to integrate all the superiorities of the government to strengthen its roles such as service,performance and function to drive the social development actively.Hence,the social public administration will take this opportunity to optimize the cyber information service platform to make the civic administration oriented to the social development to maximize its functions of organization,coordination and service to protrude the ascendancy of the web era so as to lay a solid foundation for the leap development of the public administration.展开更多
Background Social media listening is a new approach for gathering insights from social media platforms about users experiences.This approach has not been applied to analyse discussions about Alzheimer's disease(AD...Background Social media listening is a new approach for gathering insights from social media platforms about users experiences.This approach has not been applied to analyse discussions about Alzheimer's disease(AD)in China.Aims We aimed to leverage multisource Chinese data to gain deeper insights into the current state of the daily management of Chinese patients with AD and the burdens faced by their caregivers.Methods We searched ninemainstreampublic onlineplatforms in China fromSeptember2010 to March 2024.Natural language processing tools were used to identify patients and caregivers,and categorise patients by disease stage forfurther analysis.We analysed the current state of patient daily management,including diagnosis and treatment,choice oftreatment scenarios,patient safetyand caregiverconcerns.Results Atotal of 1211patientswithAD(66% female,82% aged 60-90)and 756caregiversfor patients with AD were identified from 107556 online sources.Most patients were derived from online consultation platforms(43%),followed by bulletin board system platforms(24%).Among the patients categorised into specific disease stages(n=382),42% were in the moderate stage.The most frequent diagnostic tools included medical history(97%)and symptoms(84%).Treatment options for patients with AD primarily included cholinesterase inhibitors,N-methyl-D-aspartate receptor antagonists and antipsychotics.Both quantitative and qualitative analysis of patients whoexperiencedwandering(n=92)indicated a higher incidence of wandering during the moderate stage of the disease.Most caregivers were family members,with their primary concerns focusing on disease management and treatment(90%),followed by daily life care(37%)and psychosocial support(25%).Conclusions Online platform data provide a broad spectrum of real-world insights into individuals affected byAD in China.This study enhances our understanding of the experiences of patients with AD and their caregivers,providing guidance for developing personalised interventions,providing advicefor caregivers and improving care for patients with AD.展开更多
Two artificial agents(a humanoid robot and a virtual human) are enriched with various similar intelligence,autonomy, functionalities and interaction modalities. The agents are integrated in the form of a cyber-physica...Two artificial agents(a humanoid robot and a virtual human) are enriched with various similar intelligence,autonomy, functionalities and interaction modalities. The agents are integrated in the form of a cyber-physical-social system(CPSS) through a shared communication platform to create a social ecology. In the ecology, the agents collaborate(assist each other) to perform a real-world task(search for a hidden object)for the benefits of humans. A robot-virtual human bilateral trust model is derived and a real-time trust measurement method is developed. The role of taking initiative in the collaboration is switched between the agents following a finite state machine model triggered by bilateral trust, which results in a mixedinitiative collaboration. A scheme is developed to evaluate the performance of the agents in the ecology through the CPSS.The results show that the robot and the virtual human perform satisfactorily in the collaboration through the CPSS. The results thus prove the effectiveness of the real-world ecology between artificial agents of heterogeneous realities through a shared platform based on trust-triggered mixed-initiatives. The results can help develop adaptive social ecology comprising intelligent agents of heterogeneous realities to assist humans in various tasks through collaboration between the agents in the form of a CPSS.展开更多
Purpose:Nowadays,public opinions during public emergencies involve not only textual contents but also contain images.However,the existing works mainly focus on textual contents and they do not provide a satisfactory a...Purpose:Nowadays,public opinions during public emergencies involve not only textual contents but also contain images.However,the existing works mainly focus on textual contents and they do not provide a satisfactory accuracy of sentiment analysis,lacking the combination of multimodal contents.In this paper,we propose to combine texts and images generated in the social media to perform sentiment analysis.Design/methodology/approach:We propose a Deep Multimodal Fusion Model(DMFM),which combines textual and visual sentiment analysis.We first train word2vec model on a large-scale public emergency corpus to obtain semantic-rich word vectors as the input of textual sentiment analysis.BiLSTM is employed to generate encoded textual embeddings.To fully excavate visual information from images,a modified pretrained VGG16-based sentiment analysis network is used with the best-performed fine-tuning strategy.A multimodal fusion method is implemented to fuse textual and visual embeddings completely,producing predicted labels.Findings:We performed extensive experiments on Weibo and Twitter public emergency datasets,to evaluate the performance of our proposed model.Experimental results demonstrate that the DMFM provides higher accuracy compared with baseline models.The introduction of images can boost the performance of sentiment analysis during public emergencies.Research limitations:In the future,we will test our model in a wider dataset.We will also consider a better way to learn the multimodal fusion information.Practical implications:We build an efficient multimodal sentiment analysis model for the social media contents during public emergencies.Originality/value:We consider the images posted by online users during public emergencies on social platforms.The proposed method can present a novel scope for sentiment analysis during public emergencies and provide the decision support for the government when formulating policies in public emergencies.展开更多
The article deals with the topical issue of social media regulation.It is based on the libertarian theory of economic freedom because,in our understanding,it allows the elaboration of a future-oriented human rights ba...The article deals with the topical issue of social media regulation.It is based on the libertarian theory of economic freedom because,in our understanding,it allows the elaboration of a future-oriented human rights based-on regulatory approach.This approach is premised on both freedom of speech and the right to private initiative protection in contemporary media environment.In the analysis,the recently structured Facebook and Instagram Oversight Board for Content Decisions are also discussed.The article presents arguments for the establishment of an internal body(arbitration)that can practically resolve disputes among participants and between participants and any social media platform on a regular basis.Such a body can also support the effective application of the media codes of conduct without governmental involvement and may strengthen self-regulation of platforms.展开更多
随着社交网络平台的迅速发展,网络欺凌问题日益突出,文本与图片相结合的多样化网络表达形式提高了网络欺凌的检测和治理难度.构建了一个包含文本和图片的中文多模态网络欺凌数据集,将BERT(bidirectional encoder representations from t...随着社交网络平台的迅速发展,网络欺凌问题日益突出,文本与图片相结合的多样化网络表达形式提高了网络欺凌的检测和治理难度.构建了一个包含文本和图片的中文多模态网络欺凌数据集,将BERT(bidirectional encoder representations from transformers)模型与ResNet50模型相结合,分别提取文本和图片的单模态特征,并进行决策层融合,对融合后的特征进行检测,实现了对网络欺凌与非网络欺凌2个类别的文本和图片的准确识别.实验结果表明,提出的多模态网络欺凌检测模型能够有效识别出包含文本与图片的具有网络欺凌性质的社交网络帖子或者评论,提高了多模态形式网络欺凌检测的实用性、准确性和效率,为社交网络平台的网络欺凌检测和治理提供了一种新的思路和方法,有助于构建更加健康、文明的网络环境.展开更多
基金Supported by Fondazione TIM in the context of the “Facciamola Facile” initiativeby Programma Operativo Nazionale (PON)“Ricerca e Innovazione” 2014-2020-DM 1062/2021 funds
文摘Background Over the last few years,the rapid advancement of technology has led to the development of many approaches to digitalization.In this respect,metaverse provides 3D persistent virtual environments that can be used to access digital content,meet virtually,and perform several professional and leisure tasks.Among the numerous technologies supporting the metaverse,immersive Virtual Reality(VR)plays a primary role and offers highly interactive social experiences.Despite growing interest in this area,there are no clear design guidelines for creating environments tailored to the metaverse.Methods This study seeks to advance research in this area by moving from state-of-the-art studies on the design of immersive virtual environments in the context of metaverse and proposing how to integrate cutting-edge technologies within this context.Specifically,the best practices were identified by i)analyzing literature studies focused on human behavior in immersive virtual environments,ii)extracting common features of existing social VR platforms,and iii)conducting interviews with experts in a specific application domain.Specifically,this study considered the creation of a new virtual environment for MetaLibrary,a VR-based social platform aimed at integrating public libraries into metaverse.Several implementation challenges and additional requirements have been identified for the development of virtual environments(VEs).These elements were considered in the selection of specific cutting-edge technologies and their integration into the development process.A user study was also conducted to investigate some design aspects(namely lighting conditions and richness of the scene layout)for which deriving clear indications from the above analysis was not possible because different alternative configurations could be chosen.Results The work reported in this paper seeks to bridge the gap between existing VR platforms and related literature in the field,on the one hand,and requirements regarding immersive virtual environments for the metaverse,on the other hand,by reporting a set of best practices which were used to build a social virtual environment that meets users'expectations and needs.Conclusions Results suggest that carefully designed virtual environments can positively affect user experience and interaction within metaverse.The insights gained from this study offer valuable cues for developing immersive virtual environments for the metaverse to deliver more effective and engaging experiences.
基金The authors are thankful to the Deanship of Scientific Research at Najran University for funding this work under the Research Collaboration Funding program grant coder NU/RC/SERC/11/5.
文摘Thalassemia syndrome is a genetic blood disorder induced by the reduction of normal hemoglobin production,resulting in a drop in the size of red blood cells.In severe forms,it can lead to death.This genetic disorder has posed a major burden on public health wherein patients with severe thalassemia need periodic therapy of iron chelation and blood transfusion for survival.Therefore,controlling thalassemia is extremely important and is made by promoting screening to the general population,particularly among thalassemia carriers.Today Twitter is one of the most influential social media platforms for sharing opinions and discussing different topics like people’s health conditions and major public health affairs.Exploring individuals’sentiments in these tweets helps the research centers to formulate strategies to promote thalassemia screening to the public.An effective Lexiconbased approach has been introduced in this study by highlighting a classifier called valence aware dictionary for sentiment reasoning(VADER).In this study applied twitter intelligence tool(TWINT),Natural Language Toolkit(NLTK),and VADER constitute the three main tools.VADER represents a gold-standard sentiment lexicon,which is basically tailored to attitudes that are communicated by using social media.The contribution of this study is to introduce an effective Lexicon-based approach by highlighting a classifier calledVADERto analyze the sentiment of the general population,particularly among thalassemia carriers on the social media platform Twitter.In this study,the results showed that the proposed approach achieved 0.829,0.816,and 0.818 regarding precision,recall,together with F-score,respectively.The tweets were crawled using the search keywords,“thalassemia screening,”thalassemia test,“and thalassemia diagnosis”.Finally,results showed that India and Pakistan ranked the highest in mentions in tweets by the public’s conversations on thalassemia screening with 181 and 164 tweets,respectively.
基金National Natural Science Foundation of China(Grant No.7167030951).
文摘This study examines the impact of communication on investors’trading frequency based on a unique dataset drawn from a Chinese social trading platform.We find robust evidence that real-account portfolio owners on the platform trade more frequently under the influence of the comments posted by their leaders(the owners of portfolios they have followed).Moreover,portfolio owners are more sensitive to the quantity than to the tone of leaders’comments.Finally,both trading frequency and leaders’comments negatively impact portfolio owners’future performance.Our find-ings support the notion that social interaction promotes active investment strategies.
文摘The cyber development of government service platform is just to integrate all the superiorities of the government to strengthen its roles such as service,performance and function to drive the social development actively.Hence,the social public administration will take this opportunity to optimize the cyber information service platform to make the civic administration oriented to the social development to maximize its functions of organization,coordination and service to protrude the ascendancy of the web era so as to lay a solid foundation for the leap development of the public administration.
基金funded by the Ministry of Science and Technology of the People's Republic of China(2021ZD0201804,GW).
文摘Background Social media listening is a new approach for gathering insights from social media platforms about users experiences.This approach has not been applied to analyse discussions about Alzheimer's disease(AD)in China.Aims We aimed to leverage multisource Chinese data to gain deeper insights into the current state of the daily management of Chinese patients with AD and the burdens faced by their caregivers.Methods We searched ninemainstreampublic onlineplatforms in China fromSeptember2010 to March 2024.Natural language processing tools were used to identify patients and caregivers,and categorise patients by disease stage forfurther analysis.We analysed the current state of patient daily management,including diagnosis and treatment,choice oftreatment scenarios,patient safetyand caregiverconcerns.Results Atotal of 1211patientswithAD(66% female,82% aged 60-90)and 756caregiversfor patients with AD were identified from 107556 online sources.Most patients were derived from online consultation platforms(43%),followed by bulletin board system platforms(24%).Among the patients categorised into specific disease stages(n=382),42% were in the moderate stage.The most frequent diagnostic tools included medical history(97%)and symptoms(84%).Treatment options for patients with AD primarily included cholinesterase inhibitors,N-methyl-D-aspartate receptor antagonists and antipsychotics.Both quantitative and qualitative analysis of patients whoexperiencedwandering(n=92)indicated a higher incidence of wandering during the moderate stage of the disease.Most caregivers were family members,with their primary concerns focusing on disease management and treatment(90%),followed by daily life care(37%)and psychosocial support(25%).Conclusions Online platform data provide a broad spectrum of real-world insights into individuals affected byAD in China.This study enhances our understanding of the experiences of patients with AD and their caregivers,providing guidance for developing personalised interventions,providing advicefor caregivers and improving care for patients with AD.
文摘Two artificial agents(a humanoid robot and a virtual human) are enriched with various similar intelligence,autonomy, functionalities and interaction modalities. The agents are integrated in the form of a cyber-physical-social system(CPSS) through a shared communication platform to create a social ecology. In the ecology, the agents collaborate(assist each other) to perform a real-world task(search for a hidden object)for the benefits of humans. A robot-virtual human bilateral trust model is derived and a real-time trust measurement method is developed. The role of taking initiative in the collaboration is switched between the agents following a finite state machine model triggered by bilateral trust, which results in a mixedinitiative collaboration. A scheme is developed to evaluate the performance of the agents in the ecology through the CPSS.The results show that the robot and the virtual human perform satisfactorily in the collaboration through the CPSS. The results thus prove the effectiveness of the real-world ecology between artificial agents of heterogeneous realities through a shared platform based on trust-triggered mixed-initiatives. The results can help develop adaptive social ecology comprising intelligent agents of heterogeneous realities to assist humans in various tasks through collaboration between the agents in the form of a CPSS.
基金This paper is supported by the National Natural Science Foundation of China under contract No.71774084,72274096the National Social Science Fund of China under contract No.16ZDA224,17ZDA291.
文摘Purpose:Nowadays,public opinions during public emergencies involve not only textual contents but also contain images.However,the existing works mainly focus on textual contents and they do not provide a satisfactory accuracy of sentiment analysis,lacking the combination of multimodal contents.In this paper,we propose to combine texts and images generated in the social media to perform sentiment analysis.Design/methodology/approach:We propose a Deep Multimodal Fusion Model(DMFM),which combines textual and visual sentiment analysis.We first train word2vec model on a large-scale public emergency corpus to obtain semantic-rich word vectors as the input of textual sentiment analysis.BiLSTM is employed to generate encoded textual embeddings.To fully excavate visual information from images,a modified pretrained VGG16-based sentiment analysis network is used with the best-performed fine-tuning strategy.A multimodal fusion method is implemented to fuse textual and visual embeddings completely,producing predicted labels.Findings:We performed extensive experiments on Weibo and Twitter public emergency datasets,to evaluate the performance of our proposed model.Experimental results demonstrate that the DMFM provides higher accuracy compared with baseline models.The introduction of images can boost the performance of sentiment analysis during public emergencies.Research limitations:In the future,we will test our model in a wider dataset.We will also consider a better way to learn the multimodal fusion information.Practical implications:We build an efficient multimodal sentiment analysis model for the social media contents during public emergencies.Originality/value:We consider the images posted by online users during public emergencies on social platforms.The proposed method can present a novel scope for sentiment analysis during public emergencies and provide the decision support for the government when formulating policies in public emergencies.
基金The article has been prepared as a result of the research and discussions carried out within the Compact,Horizon 2020,EU project(Compact:from research to policy through raising awareness of the state of the art on social media and convergenceProject Number 762128,call:H2020-ICT-2016-2017,topic:ICT-19-2017).The authors are much indebted to Rosemary Aud Franklin,AssocSr Librarian,University of Cincinnati,for providing valuable insights and polishing the text in the process of work.
文摘The article deals with the topical issue of social media regulation.It is based on the libertarian theory of economic freedom because,in our understanding,it allows the elaboration of a future-oriented human rights based-on regulatory approach.This approach is premised on both freedom of speech and the right to private initiative protection in contemporary media environment.In the analysis,the recently structured Facebook and Instagram Oversight Board for Content Decisions are also discussed.The article presents arguments for the establishment of an internal body(arbitration)that can practically resolve disputes among participants and between participants and any social media platform on a regular basis.Such a body can also support the effective application of the media codes of conduct without governmental involvement and may strengthen self-regulation of platforms.
文摘随着社交网络平台的迅速发展,网络欺凌问题日益突出,文本与图片相结合的多样化网络表达形式提高了网络欺凌的检测和治理难度.构建了一个包含文本和图片的中文多模态网络欺凌数据集,将BERT(bidirectional encoder representations from transformers)模型与ResNet50模型相结合,分别提取文本和图片的单模态特征,并进行决策层融合,对融合后的特征进行检测,实现了对网络欺凌与非网络欺凌2个类别的文本和图片的准确识别.实验结果表明,提出的多模态网络欺凌检测模型能够有效识别出包含文本与图片的具有网络欺凌性质的社交网络帖子或者评论,提高了多模态形式网络欺凌检测的实用性、准确性和效率,为社交网络平台的网络欺凌检测和治理提供了一种新的思路和方法,有助于构建更加健康、文明的网络环境.
