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IEEE Transactions on Affective Computing
基本信息
期刊名称 | IEEE Transactions on Affective Computing IEEE T AFFECT COMPUT |
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期刊ISSN | 1949-3045 |
期刊官方网站 | https://ieeexplore.ieee.org/xpl/RecentIssue.jsp?punumber=5165369 |
是否OA | No |
出版商 | Institute of Electrical and Electronics Engineers Inc. |
出版周期 | |
文章处理费 | 登录后查看 |
始发年份 | |
年文章数 | 245 |
影响因子 | 9.6(2023) scijournal影响因子 greensci影响因子 |
中科院SCI期刊分区
大类学科 | 小类学科 | Top | 综述 |
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工程技术2区 | COMPUTER SCIENCE, ARTIFICIAL INTELLIGENCE 计算机:人工智能2区 | 是 | 否 |
COMPUTER SCIENCE, CYBERNETICS 计算机:控制论1区 |
CiteScore
CiteScore排名 | CiteScore | SJR | SNIP | ||
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学科 | 排名 | 百分位 | 15.0 | 2.645 | 3.345 |
Computer Science Software |
27/407 | 93% |
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Computer Science Human-Computer Interaction |
10/145 | 93% |
补充信息
自引率 | 11.5% |
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H-index | 47 |
SCI收录状况 | Science Citation Index Expanded |
官方审稿时间 | 登录后查看 |
网友分享审稿时间 | 数据统计中,敬请期待。 |
接受率 | 登录后查看 |
PubMed Central (PMC) | http://www.ncbi.nlm.nih.gov/nlmcatalog?term=1949-3045%5BISSN%5D |
投稿指南
期刊投稿网址 | https://www.computer.org/web/tac/author;jsessionid=754ac76dad2796cda19553ce0570 |
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收稿范围 | The IEEE Transactions on Affective Computing is a cross-disciplinary and international archive journal aimed at disseminating results of research on the design of systems that can recognize, interpret, and simulate human emotions and related affective phenomena. The journal publishes original research on the principles and theories explaining why and how affective factors condition interaction between humans and technology, on how affective sensing and simulation techniques can inform our understanding of human affective processes, and on the design, implementation and evaluation of systems that carefully consider affect among the factors that influence their usability. Surveys of existing work are considered for publication when they propose a new viewpoint on the history and the perspective on this domain. The journal covers but is not limited to the following topics: Sensing & analysis: Algorithms and features for the recognition of affective state from face and body gestures; Analysis of text and spoken language for emotion recognition; Analysis of prosody and voice quality of affective speech; Recognition of auditory and visual affect bursts; Recognition of affective state from central (e.g. fMRI, EEG) and peripheral (e.g. GSR) physiological measures; Methods for multi-modal recognition of affective state; Recognition of group emotion; Methods of data collection with respect to psychological issues as mood induction and elicitation or technical methodology as motion capturing; Tools and methods of annotation for provision of emotional corpora. (Cyber) psychology & behavior: Clarification of concepts related to ‘affective computing’ (e.g., emotion, mood, personality, attitude) in ways that facilitate their use in computing; Computational models of human emotion processes (e.g., decision-making models that account for the influence of emotion; predictive models of user emotional state); Studies on cross-cultural, group and cross-language differences in emotional expression; Contributions to standards and markup language for affective computing. Behavior Generation & User Interaction: Computational models of visual, acoustic and textual emotional expression for synthetic and robotic agents; Models of verbal and nonverbal expression of various forms of affect that facilitate machine implementation; Methods to adapt interaction with technology to the affective state of users; Computational methods for influencing the emotional state of people; New methods for defining and evaluating the usability of affective systems and the role of affect in usability; Methods of emotional profiling and adaptation in mid- to long-term interaction; Application of affective computing including education, health care, entertainment, customer service, design, vehicle operation, social agents/robotics, affective ambient intelligence, customer experience measurement, multimedia retrieval, surveillance systems, biometrics, music retrieval and generation. The articles in this journal are peer reviewed in accordance with the requirements set forth in the IEEE PSPB Operations Manual (sections 8.2.1.C & 8.2.2.A). Each published article was reviewed by a minimum of two independent reviewers using a single-anonymous peer review process, where the identities of the reviewers are not known to the authors, but the reviewers know the identities of the authors. Articles will be screened for plagiarism before acceptance. Corresponding authors from low-income countries are eligible for waived or reduced open access APCs. |
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