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Affective content analysis

Affective Image Content Analysis: A Comprehensive Survey Sicheng Zhaoy, Guiguang Dingz, Qingming Huang], Tat-Seng Chuax, Bjorn W. Schuller¤ andKurt Keutzer y yDepartment of Electrical Engineering and Computer Sciences, University of California, Berkeley, USA z School of Software, Tsinghua University, China]School of Computer and Control Engineering, University of Chinese Academy of Sciences. Affective Content Analysis of Online Video Clips with Live Comments in Chinese Abstract: Recent years have witnessed an increasing interest in online video affective content analysis, since having a better understanding of the emotions of videos can facilitate many applications including video retrieval and classification Affective content containing the amount and types of emotion and is expected to evoke audience's emotions. Affective content analysis has been conducted in many video domains, such as sports, music videos and so on. Movies constitute a large portion of the entertainment industry state-of-the-art papers on affective video content analysis, this work confronts the ideas and models of psychology, sociology, neuroscience, and computer science. The concepts of aesthetic emotions and emotion induction, as well as the different representations of emotions are introduced, based on psychological and sociological theories

Hanjalic A., Xu. L.-Q.: User-oriented affective video content analysis, IEEE Workshop on Content-Based Access of Image and Video Libraries 2001 (CBAIVL 2001), pp. 50-57, December 2001 Google Schola Affective content analysis is necessary to represent a user's preferences in various applications such as video data retrieval and video abstraction. In this paper, we propose a new method to.

In this paper, affective content analysis of music video clips is performed to determine the emotion they can induce in people. To this end, a subjective test was developed, where 32 participants.. semantic analysis level [1]. To deal with a user's preferences effectively in video retrieval and video abstraction, it is desirable to detect affective content from video data. In other words, if affective content is analyzed, a user can retrieve the most interesting video clips or watch most exciting segments of video [1]

Affective Content Analysis of Online Video Clips with Live

and implicit video affective content analysis, as well as the existing benchmark datasets for video affective content analysis. The paper concludes with a discussion of chal-lenges and future research directions. To the best of our knowledge, this work is the first paper to provide a comprehensive review of video affective content analysis Affective Content Analysis of Music Video Clips Ashkan Yazdani Multimedia Signal Processing Group (MMSPG) Ecole Polytechnique Fédérale de Lausanne (EPFL) 1015 Lausanne, Switzerland ashkan.yazdani@epfl.ch Krista Kappeler Multimedia Signal Processing Group (MMSPG) Ecole Polytechnique Fédérale de Lausanne (EPFL) 1015 Lausanne, Switzerlan The affective content analysis includes analyzing four different moods of students', namely: High Positive Affect, Low Positive Affect, High Negative Affect, and Low Negative Affect. Engagement scores have been calculated based upon the four moods of students as predicted by the proposed method

Affective video content analysis has attracted a lot of attention recently. However, it faces various challenges such as the gap between intrinsic visual-aural features and spontaneous human emotional response, as well as ubiquitously existed label noise in affective annotations Video affective content analysis can be divided into two approaches: direct and implicit. Direct approaches infer the affective content of videos directly from related audiovisual features In this paper, affective content analysis of music video clips is performed to determine the emotion they can induce in people. To this end, a subjective test was developed, where 32 participants watched different music video clips and assessed their induced emotions

Flexible Presentation of Videos Based on Affective Content Analysis 369 and outsider. Wang et al. presented an approach for event driven web video summarization by tag localization and key-shot mining in [4], and turned a movie clip to comics automatically in [5]. Meanwhile, affective image and video content analysis has been paid muc The Affective Intonationprocedure aims to mimic the human coders' judgments by ordering each word's wordscore on its sequential location in an open-ended response and detecting changes in these patterns. Affective Intonationstarts with a word's wordscore as defined in Equation 1 Writer 1658. Comment: Excellent marking service, definitely recommend this service, the marker also tells you what your work is graded at giving you an idea of where you are at, so you have Time to improve and gain a better mark if needed, explains throughly of where you can improve, from start to finish a lot of feedback from structure, clarity, spelling grammar etc Analysis of content to measure affect and its experiences is a growing multidisciplinary research area that still has little cross-disciplinary collaboration

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In this paper, we propose an approach for affective characterization of movie scenes based on the emotions that are actually felt by spectators. Such a representation can be used to characterize the emotional content of video clips in application areas such as affective video indexing and retrieval, and neuromarketing studies The goal of affective video content analysis is to automatically predict the reaction of audience elicited by videos. The criteria, which can reflect users' feelings, include the valence and arousal values and other parameters , .In this paper, we use the MediaEval 2017 dataset for the model training and testing A large number of emotional states can be represented using this 2-D model and many studies about affective content analysis use this simplified model as for example in [5] or in [7]. Similar to the 3D P-A-D model, only some parts of the 2-D space is relevant as shown by figure 1 (b).In this paper, the P-A-D model of emotion is used and. FFECTIVEvideo content analysis aims at auto- matic recognition of emotions elicited by videos. It has a large number of applications, including mood- based personalized content delivery, video index- ing, video indexing, and summarization (e.g.,)

Hierarchical affective content analysis in arousal and

  1. Our use of advanced content analysis techniques to code affective content of articles and blog posts continues to extend recent organizational research on social perceptions management that recognizes the importance of trying to open the black box that is often present in strategy research..
  2. Content analysis takes into following elements when analyzing issues: Major elements of content analysis (Source: Kohlbacher, 2005) Steps of content analysis. Content analysis in qualitative research is carried out by recording the communication between the researcher and its subjects. One can use different modes such as transcripts of.
  3. MMDQEN: Multimodal Deep Quality Embedding Network for Affective Video Content Analysis. This is our implementation of MMDQEN associated with the following paper: Affective video content analysis via multimodal deep quality embedding network, Yaochen Zhu, Zhenzhong Chen, Feng Wu Accepted as a journal paper in IEEE Trans. Affect. Compute, 2020.
  4. 2nd Workshop on Affective Content Analysis Proceedings of the 2nd Workshop on Affective Content Analysis (AffCon 2019) co-located with Thirty-Third AAAI Conference on Artificial Intelligence (AAAI 2019) Honolulu, USA, January 27, 2019. Edited by . Niyati Chhaya * Kokil Jaidka ** Atanu Sinha * Lyle Ungar *** * Adobe Research, Indi

Analysis of content to measure affect and its experiences is a growing multidisciplinary research area that still has little cross-disciplinary collaboration. The artificial intelligence (AI) and computational linguistics (CL) communities are making strides in identifying and measuring affect from user signals especially in language, while the. The 4th Workshop on Affective Content Analysis @ AAAI 2021. We made a cool poster so of course, that deserves a new blogpost Collaborative creativity. If I wasn't organizing the workshop, I'd love to explore the CL-Aff Diplomacy dataset and try out some ideas. But you don't have to worry about organizing it affective content analysis, have also been conducted using the spontaneous response of users watching the videos (e.g., facial recordings, physiological responses). However, this topic has already been investigated in [7]. This paper focuses rather on direct video affective content analysis studies, usin Recently, with the explosive growth of visual data, extensive research efforts have been dedicated to affective image content analysis (AICA). In this paper, we review the state-of-the-art methods comprehensively with respect to two main challenges -- affective gap and perception subjectivity

Affective Video Content Analysis: A Multidisciplinary Insigh

The second meta-analysis reports a random-effects meta-analysis of 46 studies (N = 13,501). Moderators were examined and revealed that study design (i.e., survey versus experiment) moderated the impact of instructor clarity on affective learning. No significant moderators were found for cognitive learning A ective content analysis have been conducted in many video domains, such as sports, MTV and so on. Movie affective content analysis is still a challenging task due to the incompact video structure and too much emotions romanced in a movie, but it can provide an indexing for users to access their interested content directly The content of the responses provides an index of the affective and cognitive speech acts generated by the patient's health theory or belief. The analysis of verbalizations as an index to the speaker's affective states and cognitive operations has a long tradition in functional and behavioral psychology [9-14] AFFECTIVE CONTENT ANALYSIS IN COMEDY AND HORROR VIDEOS BY AUDIO EMOTIONAL EVENT DETECTION (WedPmPO1) Author(s) : Min Xu (Nanyang Technological University, Singapore) Liang−Tien Chia (Nanyang Technological University, Singapore) Jesse Jin (University of Newcastle, Australia) Abstract : We study the problem of affective content analysis. In this paper we think of affective contents as thos

In this paper, we propose an approach for affective characterization of movie scenes based on the emotions that are actually felt by spectators. Such a representation can be used to characterize the emotional content of video clips in application areas such as affective video indexing and retrieval, and neuromarketing studies. A dataset of 64 different scenes from eight movies was shown to. Content analysis is the study of documents and communication artifacts, which might be texts of various formats, pictures, audio or video. Social scientists use content analysis to examine patterns in communication in a replicable and systematic manner. One of the key advantages of using content analysis to analyse social phenomena is its non-invasive nature, in contrast to simulating social. affective analysis is an emerging research field that targets this problem of affective content analysis of videos. The affective content of a video is defined as the intensity (i.e., arousal) and type (i.e., valence) of emotion (both are referred to as affect) that are expected to arise in the user while watching that video [7] Affect analysis of content to measure emotions and its experiences is a multidisciplinary research area with limited cross-disciplinary collaboration. Other disciplines have adopted psychological models of affect - Artificial Intelligence (AI), Computational Linguistics (CL) and Human-computer Interaction (HCI) - to conceptualiz affective, and behavioral dimensions of relationship development and deterioration as proposed by Knapp (1978). Before the session began, the respondents completed a form that This technique of content analysis classifies signs according to their meaning. Mor

Affective Video Content Analysis SpringerLin

(PDF) Affective Content Analysis in Comedy and Horror

Affective and Content Analysis of Online Depression Communities. Nguyen Thin, Phung Dinh, Dao Bo, Svetha Venkatesh, Michael Berk IEEE Transactions on Affective Computing | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Published : 2014 DOI: 10.1109/TAFFC.2014.2315623. Cite. On the one hand, there is support that expressing affective content can attenuate the affective experiences, e.g., via 'affect labelling'. When individuals use affect labelling and put their emotions into words this can result in a decrease in the intensity of the affective, often negative, experience (see, e.g., [ 10 - 12 ]) As emotion is a subjective concept, affective analysis involves multidisciplinary understanding of human perceptions and behaviors. Furthermore, emotions are often jointly expressed and perceived through multiple modalities. Multi-modal data fusion and complementation need to be explored Aims: The aim of this study was to explore the specific burdens experienced by caregivers of patients with schizophrenia and affective disorders. Methods: A qualitative study was conducted by semi-structured interviews with 45 caregivers of patients with schizophrenia and affective disorders. Data were analysed by qualitative content analysis

The aim of thematic analysis is to identify themes within the data, in this case, themes relating to the cognitive factors which influenced the generation of an affective response. Unlike content analysis, thematic analysis is an inductive process because the categories into which the themes will be classified have not been predetermined prior. AFFECTIVE TRENDS 3 Music and Affective Phenomena: A 20-year content and bibliometric analysis of research in three eminent journals Affective phenomena are central to a comprehensive understanding of musical processing and experience, and are a frequent topic of investigation among scholars in music education (2019) Affective video content analysis based on multimodal data fusion in heterogeneous networks [ ️ Visual ️ Audio] (2019) Audio-visual emotion fusion (AVEF): A deep efficient weighted approach [ ️ Visual ️ Audio] Neural Networks (2015) Towards an intelligent framework for multimodal affective data analysis

CiteSeerX - Document Details (Isaac Councill, Lee Giles, Pradeep Teregowda): Abstract—This paper looks into a new direction in video content analysis - the representation and modeling of affective video con-tent. The affective content of a given video clip can be defined as the intensity and type of feeling or emotion (both are referred to as affect) that are expected to arise in the user. Every year, I organize the Affective Content Analysis workshop @ AAAI and its Shared Task. In 2020, I organized a Shared Task on Interactional Affect (The OffMyChest Shared Task) at the third Affective Content Analysis workshop @ AAAI in Feb 2020 together with Adobe and the University of Pennsylvania Soleymani M, Chanel G, Kierkels JJM, et al.: Affective ranking of movie scenes using physiological signals and content analysis. In: 2nd ACM workshop on Multimedia semantics. New York, NY, USA: ACM, 2008; 32-39. Publisher Full Text Soleymani M, Yang Y, Irie G, et al.: Guest editorial: Challenges and perspectives for affective analysis in. Categorical affective content analysis is more suitable to be called as affective classification. Although the flexibility of these methods is limited, they are simple, and easy to build. Dimensional affective content analysis commonly employs the dimensional affective model for affective state computation

Jeong J.-W., and Lee D.-H., Automatic image annotation using affective vocabularies: Attribute-based learning approach, Journal of Information Science (2014), 0165551513501267. [16] Kang H.-B., Affective content detection using HMMs, Proceedings of the eleventh ACM international conference on, Multimedia Publishing, (2003), 259-262. [17 Affective video content analysis aims at the automatic recognition of emotions elicited by videos. It has a large number of applications, including mood based personalized content recommendation , video indexing , and efficient movie visualization and browsing .Beyond the analysis of existing video material, affective computing techniques can also be used to generate new content, e.g., movie. Chapter 9: Textual Analysis I. Introduction A. Textual analysis is the method communication researchers use to describe and interpret the characteristics of a recorded or visual message. 1. The purpose of textual analysis is to describe the content, structure, and functions of the messages contained in texts. 2 Most of the existing works on multimedia analysis focused on cognitive content understanding, such as scene understanding, object detection, and recognition. Recently, with a significant demand for emotion representation in artificial intelligence, multimedia affective analysis has attracted increasing research efforts from both academic and. Cognitive/psychological perspective on affective content analysis; Affective multimedia applications; Submission should be in ICME 2013 format and maximum 6 pages. Please, consult the ICME website for the exact formatting and template. Each submission will receive at least two reviews by expert reviewers in the field in addition to a meta.

(PDF) Affective content analysis of music video clip

Students' affective content analysis in smart classroom

  1. Global Affective Computing Market: Snapshot. The global affective computing market is envisioned to create high growth prospects on the back of the rising deployment of machine and human interaction technologies. With enabling technologies already making a mark with their adoption in a range of industry verticals, it could be said that the market has started to evolve
  2. The global affective computing market size is expected to reach USD 284.73 Billion at a steady CAGR of 32.5% in 2028, according to latest analysis by Emergen Research. Steady market revenue growth can be attributed to growing demand for telemedicine and increasing need to remotely assess patient's health
  3. Recently, video affective content analysis attracts more and more research efforts. Most of the existing methods map low-level affective features directly to emotions by applying machine learning. Compared to human perception process, there is actually a gap between low-level features and high-level human perception of emotion
  4. Affective Content Analysis and Applications of Large-Scale Multimedia Data 1. Scope and Topics This ICIG 2019 special session aims to gather high-quality contributions reporting the most recent progress on affective content analysis of large-scale multimedia data and its wide applications. It targets a mixed audience of researchers and produc

Multimodal Deep Denoise Framework for Affective Video

Keywords: Affective Content Analysis, Dimensional Affective Model, Support Vector Regression, Personalized Affective Analysis. 1 Introduction To date, tons of works have been reported on affective music, movie content analysis [1-6]. Similar to music and movie that are important favorite pastimes, MTV (Musi Using script to directly access video content avoids complex video analysis. Thirdly, audio event detection is utilized to assist affective content detection. Compared with traditional video semantic analysis, affective content analysis puts much more emphasis on the audience's reactions and emotions A Brief History of Content Analysis. Historically, content analysis was a time consuming process. Analysis was done manually, or slow mainframe computers were used to analyze punch cards containing data punched in by human coders. Single studies could employ thousands of these cards Therefore, affective behavior is measured with bi-polar scales and cognitive behavior is measured with multiple-choice, matching or fill-in items. Content analysis and protocol analysis of concurrent verbal reports are used to identify affective and cognitive behavior patterns during search tasks (Nahl, 2001)

Affective and Content Analysis of Online Depression Community. IEEE Transactions on Affective Computing (TAC), 5(3), 217-226, 2014.[ISI, 5-year IF: 4.585]. Thin Nguyen, Bo Dao, Dinh Phung, Svetha Venkatesh and Michael Berk. Online Social Capital: Mood, Topical and Psycholinguistic Analysis .ICWSM, 2013. Pages 449-456 The Chieti Affective Action Videos (CAAV) is a new database designed for the experimental study of emotions in psychology. The main goal of the CAAV is to provide a wide range of standardized.. Cognitive and affective annotation of media and advertising: Multimodal annotation of content - movies, sports, games and advertisement - powered by AI models to generate greater contextual knowledge of content - what is the content about (cognitive) and how is it likely going to affect the consumer (affective) Affective and content analysis of online depression communities Nguyen, Thin, Phung, Dinh, Dao, Bo, Venkatesh, Svetha and Berk, Michael 2014, Affective and content.

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Video Affective Content Analysis: A Survey of State-of-the

  1. - The purpose of this paper is to identify specific cognitive and affective responses in mall experience, as well as their antecedents, moderators and behavioural outcomes. , - The paper is based on content analysis technique. Data were obtained through in-depth interviews conducted from February 2013 to January 2014. , - The study reports the identification of efficiency and confusion.
  2. When compared by content analysis, the manics used more words reflecting a concern with power and achievement. These results imply that depressive speech tends to be more vague and qualified and to show considerable self-preoccupation, while manic speech tends to be colorful and concrete and to show more concern with things than with people
  3. Affective analysis of social multimedia is attracting growing attention from industry and businesses that provide social networking sites, content-sharing services, distribute and host the media. The first ASMMC workshop has been successfully held in Xi'an, China on September 21 2016
  4. In AAAI-18 Workshop on Affective Content Analysis (AFFCON 2018) @inproceedings{ding2018affect, title={Why is an Event Affective? Classifying Affective Events based on Human Needs}, author={Ding, Haibo and Jiang, Tianyu and Riloff, Ellen}, booktitle={AAAI-18 Workshop on Affective Content Analysis (AFFCON 2018)}, year={2018}.
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Affective content analysis of music video clips

  1. dynamic affective content while fMRI activity was recorded. Across all participants there was a large-scale tracking of affective content in emotion processing regions and the default mode network. Anxious and depressed the analysis of the overall effects for valence and arousal. Parameter estimate
  2. ing or emotion AI) is the use of natural language processing, text analysis, computational linguistics, and biometrics to systematically identify, extract, quantify, and study affective states and subjective information. Sentiment analysis is widely applied to voice of the customer materials such as reviews and survey responses, online and social.
  3. Affective definition is - relating to, arising from, or influencing feelings or emotions : emotional. How to use affective in a sentence
  4. By stimulating the human affective response mechanism, affective video content analysis extracts the affective information contained in videos, and, with the affective information, natural, user-friendly, and effective MV access strategies could be developed. In this paper, a novel integrated system (i.MV) is proposed for personalized MV.
  5. -ing, multimedia content analysis. Due to the variety of the different affective representations (categorical vs dimensional, discrete vs continuous.
  6. Content Analysis, Exploratory Factor Analysis (EFA) and Confirmatory Composite Analysis (CCA) using Partial Least Square (PLS) were used to explore and predict the data. The EFA output generated three dimensions with 21 items. The dimensions are cognitive SC, affective SC and a conative SC that reflects the notion of sustainable consumption

Automating Content Analysis of Open-Ended Responses

A Computer-Aided Affective Content Analysis of Nanotechnology Newspaper Articles. Robert Davis - 2011 - NanoEthics 5 (3):319-334. The Mark of the Mental. Richard Brown - 2007 - Southwest Philosophy Review 23 (1):117-124. Qualitative Beliefs, Wide Content, and Wide Behavior The General Inquirer: A computer system for content analysis and retrieval based on the sentence as a unit of information. Behavioral Science, 7(4), 484-498. Lexicoder Sentiment Dictionary. Lori Young and Stuart Soroka. 2012. Affective News: The Automated Coding of Sentiment in Political Texts, Political Communication 29: 205-231 Analysis. The visual content analysis was conducted manually by one coder. Every resource was scanned for the presence of visual content. If there was visual content, each visual was checked for the number of men, women, boys, and girls, and the profession and activity of each person in the visual (see S1 Appendix 1 for the code books). The profession of each individual was studied to identify.

Responding to Cognitive and Affective Content - Perfect

  1. Affective analysis of social multimedia is attracting growing attention from industry and businesses that provide social networking sites, content-sharing services, distribute and host the media. This workshop focuses on the analysis of affective signals in social multimedia (e.g., twitter, weichat, weibo, youtube, facebook, etc)
  2. The purpose of this study was to measure affective learning after viewing an asynchronously delivered simulation, reflecting (metacognition), and writing about the experience. Research in agricultural education is devoid of writing as an assessment tool to measure learning in the affective domain. Content analysis of 83 reflectiv
  3. ation based on partisan cues
  4. Affective fallacy, according to the followers of New Criticism, the misconception that arises from judging a poem by the emotional effect that it produces in the reader.The concept of affective fallacy is a direct attack on impressionistic criticism, which argues that the reader's response to a poem is the ultimate indication of its value.. Those who support the affective criterion for.
  5. Animated GIFs are widely used on the Internet to express emotions, but automatic analysis of their content is largel... in Affective Computing Rosalind W. Picard · Weixuan 'Vincent' Che
  6. peripheral physiological signals and multimedia content analysis. Finally, decision fusion of the classification results from the different modalities is performed. The dataset is made publicly available and we encourage other researchers to use it for testing their own affective state estimation methods

In this situation a content analysis of the scales' items appeared to be a useful instrument in approaching the problemhow AT relates to cognitive and affective individual difference measures.The following scales were included in our study: need for closure, need for structure, need for cognition, need for evaluation, need for precision. A meta-analysis was performed to evaluate overall strengths of relation between self-efficacy (SE) and functioning (pain severity, functional impairment, affective distress) in chronic pain samples, as well as potential moderating effects of sociodemographic characteristics and methodologic factors on these associations PAT RESEARCH is a B2B discovery platform which provides Best Practices, Buying Guides, Reviews, Ratings, Comparison, Research, Commentary, and Analysis for Enterprise Software and Services. We provide Best Practices, PAT Index™ enabled product reviews and user review comparisons to help IT decision makers such as CEO's, CIO's, Directors. Content intelligence is a content marketing approach that uses AI-powered systems and software to transform content data and enterprise data into actionable insights to establish an effective content strategy. With content intelligence, organizations can create high value, data-driven, targeted and conversion-focused content The focus of the talk will be on content analysis for affective characterization and not on affect sensing. At the end, I will give recommendations on affective corpora development and present an example of public affective content corpus development, i.e., Violence scenes detection at Mediaeval benchmarking campaign

AffCon 2020 : AAAI-20 Workshop on Affective Content Analysi

Special session on Multimodal Affective Analysis for Human-Machine Interfaces and Learning Environments Affective analysis is a broad research area that focuses on the recognition, interpretation, processing and simulation of human affect, i.e., feelings or emotions multiple studies used multimedia content analysis (MCA) for automated affective tagging of videos. Hanjalic and Xu [29] introduced personalized content delivery as a valuable tool in affective indexing and retrieval systems. In order to represent affect in video, they first selected video—and audio—content features based on their relatio The Triangular Analysis is a tool that Margaret Schuler (1986) developed to help people working in advocacy in performing a strategic analysis of the issues they are working on (VeneKlasen & Miller, 2002). We consider the Triangle Analysis one of the most important strategic analysis tools to use throughout our advocacy campaigns Seasonal Affective Disorders Market 2021 Straits Research Market report Provides detailed analysis of the Seasonal Affective Disorders market with Top Keyplayers, Product types, Application, geographical regions. Experts have studied the historical data and compared it with the current market situation.The Research Report covers the industry future trends, risks, market status, development.

Affective Characterization of Movie Scenes Based on

Affective prosody recognition is an important area of research in autism spectrum conditions where difficulties in social cognition have been frequently observed. To probe into the mixed results re..

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