2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)最新文献_第7页

Multi-Attribute Data Visualization Analysis Model for Multimedia 多媒体多属性数据可视化分析模型

2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI: 10.1109/BESC48373.2019.8963246

Jun Wu, Yaoxin Chen

引用次数: 0

Adaptive Multi-Threshold Energy-Aware Virtual Machine Consolidation in Cloud Data Center 云数据中心的自适应多阈值能量感知虚拟机整合

2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-10-01 DOI: 10.1109/BESC48373.2019.8963569

Yingyue Hu, Ding Ding, Kaixuan Kang, Tingting Li

引用次数: 0

Social Transparency in Enterprise Information Systems: Peculiarities and Assessment Factors 企业信息系统的社会透明度:特点与评估因素

2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-09-23 DOI: 10.1109/BESC48373.2019.8963048

Tahani Alsaedi, Angelos Stefanidis, Keith Phalp, Raian Ali

{"title":"Social Transparency in Enterprise Information Systems: Peculiarities and Assessment Factors","authors":"Tahani Alsaedi, Angelos Stefanidis, Keith Phalp, Raian Ali","doi":"10.1109/BESC48373.2019.8963048","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8963048","url":null,"abstract":"Social transparency within an organisation refers to the intentional sharing by individuals of information relating to themselves and their group to others in the workplace. This includes announcing personal interests, activity status, priorities and personal achievements. Such transparency is typically intended to increase relatedness, motivation and trust amongst colleagues. Social networking features are being embedded within organisational information systems, allowing an online version of social transparency. An ad-hoc implementation of such transparency can pose issues such as information overload, motivating unwanted grouping amongst colleagues and increasing pressure to perform in a certain manner. This results in organisational problems such as reduced productivity, unproductive competition and high turnover rates. Our ultimate aim is to address these issues by proposing an assessment method for online social transparency to detect and minimise its negative impact on employees and organisations. In this paper, we report on empirical study results and present (1) a set of peculiarities of implementing online transparency in enterprise information systems and (2) a set of essential factors that relate to the assessment process.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"120 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-09-23","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126869287","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

Makeup based on segmentation and local transfer 化妆基于分割和局部转移

2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-09-11 DOI: 10.1109/BESC48373.2019.8963094

Yuanhan Zhang, Haidong Cui, Yidong Li, Zheng Feng

引用次数: 0

Procrastination on Social Networks: Types and Triggers 社交网络上的拖延症:类型和诱因

2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-08-21 DOI: 10.1109/BESC48373.2019.8963036

A. Alblwi, Angelos Stefanidis, Keith Phalp, Raian Ali

{"title":"Procrastination on Social Networks: Types and Triggers","authors":"A. Alblwi, Angelos Stefanidis, Keith Phalp, Raian Ali","doi":"10.1109/BESC48373.2019.8963036","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8963036","url":null,"abstract":"Procrastination refers to a voluntary delay of a needed or committed task that might hurt productivity and wellbeing requirements such as self-acceptance, personal growth and positive relations with others. People might procrastinate due to a lack of motivation towards performing a task or a mismatch between the task and their skills. Social Networks Sites (SNS) are designed to provide users with the opportunity to socialise and feel relatedness despite being physically separated. SNSs design is typically equipped with a rich set of persuasive tools to encourage more social interaction. Such tools can entice procrastination when users have low self-regulation ability, and seek avoidance and mood modification. As a first step in designing persuasive features which would help people control their procrastination, there is a need to understand how existing SNS features persuade procrastination in the first place. In this paper, we conduct a multi-stage qualitative study to explore the occurrence of procrastination and the prominent features of SNS design that trigger and facilitate it. We use focus groups to explore SNS procrastination, and then get a more ecologically valid, detailed and in-context data via a ten days' diary study followed by clarification interviews. The findings shed light on prominent types of procrastination and features in SNS design that can persuade and increase, in certain contexts, the chance for procrastination.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"21 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"134618219","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 9

Fear of Missing Out (FoMO) as Really Lived: Five Classifications and one Ecology 错失恐惧症(FoMO)的真实存在:五种分类和一种生态

2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-08-21 DOI: 10.1109/BESC48373.2019.8963027

Aarif Alutaybi, J. McAlaney, E. Arden-Close, Angelos Stefanidis, Keith Phalp, Raian Ali

{"title":"Fear of Missing Out (FoMO) as Really Lived: Five Classifications and one Ecology","authors":"Aarif Alutaybi, J. McAlaney, E. Arden-Close, Angelos Stefanidis, Keith Phalp, Raian Ali","doi":"10.1109/BESC48373.2019.8963027","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8963027","url":null,"abstract":"Social media provides a platform for information sharing and dissemination and has speedily become a popular method for individuals to relate to others regardless of the time and geographical distance. However, this wealth of connectivity and availability of information may lead to the experience of the Fear of Missing Out (FoMO) that typically refers to a preoccupation of the users of social media about lost opportunities when they are offline or unable to connect and communicate as wished. Despite the recognition of the concept, studies around FoMO have used offline data collection techniques such as interviews, focus groups and surveys. This has led to a limited understanding of the lived FoMO experience and a rather simplified and coarse-grained view of the concept. In this paper, we delve into the specifics and nuances of FoMO through multi-stage qualitative research, including interviews, diary study and three focus group sessions and elaborate upon the concept and determine its various manifestations and classification. The lived experience is mainly gathered through a diary study. We present five main classifications characterising FoMO and develop an ecology for it.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-08-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"114790889","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 12

TPM: A GPS-based Trajectory Pattern Mining System 基于gps的轨迹模式挖掘系统

2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-07-05 DOI: 10.1109/besc48373.2019.8963296

Yang Cao, Jingling Yuan, Song Xiao, Qing Xie

{"title":"TPM: A GPS-based Trajectory Pattern Mining System","authors":"Yang Cao, Jingling Yuan, Song Xiao, Qing Xie","doi":"10.1109/besc48373.2019.8963296","DOIUrl":"https://doi.org/10.1109/besc48373.2019.8963296","url":null,"abstract":"With the development of big data and artificial intelligence, the technology of urban computing becomes more mature and widely used. In urban computing, using GPS-based trajectory data to discover urban dense areas, extract similar urban trajectories, predict urban traffic, and solve traffic congestion problems are all important issues. This paper presents a GPS-based trajectory pattern mining system called TPM. Firstly, the TPM can mine urban dense areas via clustering the spatial-temporal data, and automatically generate trajectories after the timing trajectory identification. Mainly, we propose a method for trajectory similarity matching, and similar trajectories can be extracted via the trajectory similarity matching in this system. The TPM can be applied to the trajectory system equipped with the GPS device, such as the vehicle trajectory, the bicycle trajectory, the electronic bracelet trajectory, etc., to provide services for traffic navigation and journey recommendation. Meantime, the system can provide support in the decision for urban resource allocation, urban functional region identification, traffic congestion and so on.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-05","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129719542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 3

An Item Recommendation Approach by Fusing Images based on Neural Networks 一种基于神经网络的图像融合项目推荐方法

2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-07-04 DOI: 10.1109/BESC48373.2019.8963237

Wei-Yan Lin, Lin Li

引用次数: 1

Combining Q&A Pair Quality and Question Relevance Features on Community-based Question Retrieval 结合问答对质量和问题相关性特征的基于社区的问题检索

2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-07-03 DOI: 10.1109/BESC48373.2019.8963362

Dong Li, Lin Li

引用次数: 0

Deep neural network-based classification model for Sentiment Analysis 基于深度神经网络的情感分析分类模型

2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC) Pub Date : 2019-07-03 DOI: 10.1109/BESC48373.2019.8963171

Donghang Pan, Jingling Yuan, Lin Li, Deming Sheng

{"title":"Deep neural network-based classification model for Sentiment Analysis","authors":"Donghang Pan, Jingling Yuan, Lin Li, Deming Sheng","doi":"10.1109/BESC48373.2019.8963171","DOIUrl":"https://doi.org/10.1109/BESC48373.2019.8963171","url":null,"abstract":"The growing prosperity of social networks has brought great challenges to the sentimental tendency mining of users. As more and more researchers pay attention to the sentimental tendency of online users, rich research results have been obtained based on the sentiment classification of explicit texts. However, research on the implicit sentiment of users is still in its infancy. Aiming at the difficulty of implicit sentiment classification, a research on implicit sentiment classification model based on deep neural network is carried out. Classification models based on DNN, LSTM, Bi-LSTM and CNN were established to judge the tendency of the user's implicit sentiment text. Based on the Bi-LSTM model, the classification model of word-level attention mechanism is studied. The experimental results on the public dataset show that the established LSTM series classification model and CNN classification model can achieve good sentiment classification effect, and the classification effect is significantly better than the DNN model. The Bi-LSTM based attention mechanism classification model obtained the optimal R value in the positive category identification.","PeriodicalId":190867,"journal":{"name":"2019 6th International Conference on Behavioral, Economic and Socio-Cultural Computing (BESC)","volume":"45 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-07-03","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"124514033","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 11