Multimedia Context Research Articles

Evaluating multimedia advertising campaign effectiveness

Companies increasingly combine multiple media outlets when launching advertising campaigns. This study employs causal forest to examine the effects of complex multimedia campaigns. The model effectively corrects for selection bias, automatically identifies informative consumer features, and performs automated data-driven consumer segmentation based on the consumer features identified. We analyze a large dataset involving around seven million consumers and four thousand covariates, and provide empirical evidence on the nonlinear effect of repeated ad exposures in the multimedia context, how such effect varies across consumer groups, and the contingent existence of multimedia synergy. We demonstrate that negligence of the selection bias and heterogeneity across segments results in suboptimal conversions and a waste of advertising resources. The analysis procedure that we propose can facilitate decision making for complex advertising campaigns to improve their effectiveness.

Conversations from Arendelle: Children’s understanding of musical affect in a narrative, multimedia context

Children’s verbatim memory for song lyrics has been broadly investigated in the psychological literature, but little is known about the developmental course of children’s ability to construct meaning from familiar multimedia songs containing both concrete and metaphorical language. The present study examined age-related change in children’s understanding of the hit song “Let It Go” using a brief comprehension measure and a semi-structured interview conducted over Zoom. Participants included 51 children from 3- to 10-year-olds whose parents reported that they were familiar with and enjoyed Frozen. Participants’ comprehension of the song was assessed using a visual comprehension measure. They then co-viewed the music video, with the researcher pausing at several time points in the song to ask how the child thought Elsa was feeling and how the child knew. A grounded analysis of participants’ responses yielded five categories that comprehensively captured the range of cues (song lyrics, non-lyrical musical elements, observable action on screen, character appearance, and non-observable narrative elements). A median split of the sample revealed that older children referenced more converging cues to explain their thinking on Elsa’s emotion during the song and that older children referenced musical cues (both lyrical and non-lyrical) significantly more than younger children.

Analysis of the Rendering of Deep and Short Art Effects Under the Multimedia Background Taking into Account the 3D Ink Rendering Algorithm

People's living standard is improving and the economy is developing rapidly, so the demand for spiritual culture is also increasing. Today, with the rapid development of information technology, 3D ink rendering technology has become an indispensable part of modern art. It is not only a visual expression and tool, but also has a great impact on people's daily life. It is based on computer language and multimedia software. Its main purpose is to express art through images, sound and text; it can also integrate various complex and creative elements to form a whole picture, thus giving the whole picture a certain sense of hierarchy. This will give people an intuitive and strong visual feeling, thus achieving the purpose of "visual communication". In 3D ink rendering technology, image processing and sound effects are the two most important aspects. Among them, there is a certain correlation between digital works and text and other multimedia contexts with strong and far-reaching art effects rendering; and the impact of color and sound effects on 3D scenes should not be ignored: from the overall perspective, the sense of picture and enhanced visual effects can enhance the virtual reality space atmosphere and enrich the visual experience; but from the specific content, this may reduce the efficiency of the rendering process. In this paper, we start from the principle of ink rendering algorithm and analyze its impact on the picture effect and color processing in combination with 3D ink rendering technology.

A Context-Based Multimedia Vocabulary Learning System for Mobile Users

Vocabulary acquisition and retention is an essential part of learning a foreign language and many learners use flashcard applications to repetitively increase vocabulary retention. However, it can be difficult for learners to remember new words and phrases without any context. In this paper, we propose a system that allows users to acquire new vocabulary with media which gives context to the words. Theoretically, this use of multimedia context should enable users to practice with interest and increased motivation, which has been shown to enhance the effects of contextual language learning. An experiment with 46 English as foreign language learners showed better retention after two weeks with the proposed system as compared to ordinary flashcards. However, the impact was not universally beneficial to all learners. An analysis of participant attributes that were gathered through surveys and questionnaires shows a link between personality and learning traits and affinity for learning with this system. This result indicates that the proposed system provides a significant advantage in vocabulary retention for some users, while other users should stay with traditional flashcard applications. The implications of this study indicate the need for the development of more personalized learning applications.

The effect of emotional labour on professional well-being among early childhood teachers based on structural equation modelling

Abstract This paper strategically classifies the emotional labor of early childhood teachers and explores the relationship between emotional labor, emotional exhaustion, occupational well-being, and occupational self-efficacy based on a five-dimensional model of teachers’ occupational well-being. A structural equation model was developed to explore the mediating effects of early childhood teachers’ psychological capital between surface behavior, passive depth behavior, and occupational well-being, using psychological capital as a mediating variable. Based on the mediation analysis of the structural equation model, parameter identification and parameter design were performed to conduct descriptive statistics, correlation and regression analyses of emotional labor and occupational well-being of kindergarten teachers occupational well-being, and to test the moderating effect of social support in the multimedia context. Deep play significantly and positively predicted the dimensions of emotional well-being, professional well-being, interpersonal harmony, environmental satisfaction, and total occupational well-being scores, i.e., β= 0.35, 0.42, 0.40, 0.21, 0.36, P<0.01.

Exploring the Construction and Practice of College English Blended Teaching Model Based on Fuzzy Comprehensive Teaching Evaluation Model

Abstract In order to explore a new English teaching mode, this paper constructs a hybrid teaching model of English in colleges and universities combined with multimedia to respond to the call for reform and innovation of teaching mode. Firstly, through analyzing three hybrid modes of teaching: complementary mode, flipped mode and cooperative mode, a multimedia-based hybrid English teaching model is constructed in combination with current multimedia technology. Secondly, the fuzzy comprehensive teaching evaluation model based on EWM-AHP-DEMATEL and the teaching quality and learning quality evaluation index system of the hybrid English teaching mode in the multimedia context were constructed. Then in the teaching evaluation system, it was found that the satisfaction of teaching materials construction after the improvement was only 85%. There is still a lot of room for improvement, but overall, all have more than 5% satisfaction improvement. In the learning evaluation system, the number of outstanding students in English class participation, English accompanying test, innovation challenge, and English practice all increased by more than 5, and the number of those needing efforts decreased by more than 3. The overall grade improved by about 12% compared to the previous semester. Finally, the conclusion found that this new teaching model can improve teaching ability and students’ English learning ability and is worth implementing in colleges and universities.

The use of traditional Chinese elements in modern interior design in the context of multimedia

Abstract Chinese traditional elements have to carry on their own inheritance and innovation in continuous social development, and this process will encounter different challenges and complex problems. In order to better integrate traditional elements into interior design, this paper analyzes the current situation of integrating traditional elements into modern interior design, uses a neural network model to explore the influence of multimedia context on the modern interior design of traditional Chinese elements, and investigates modern people’s preference for the way traditional elements are integrated into modern interior design through a questionnaire survey. The results show that the priority factors for choosing an interior design, the number of consumers aged 20-35 who prefer their favorite style in home decoration, accounts for about 40% of the total, and the cross analysis shows that the sense of atmosphere accounts for 15%, which shows that young people around 20-35 years old have the personality of the times and pursue a high quality of life. Only the age older users will consider comfort. It can be seen that interior design with traditional elements is more in line with the preferences of older people. Inheritance and innovation of traditional Chinese culture is a huge challenge, and the reasonable integration of traditional and modern science needs to make attempted more.

Research on Innovation of Translation Teaching and Translation Strategies for College Students in Multimedia Background

Abstract In the multimedia context, it is important to enrich the teaching forms, challenge the traditional teaching concepts and realize the innovation of education mode. In this paper, a detailed review of translation strategies for college students in the multimedia context is presented, and the traditional GLR translation teaching analysis algorithm is analyzed. To compensate for the shortcomings of low translation teaching efficiency caused by over-fitting in the traditional GLR translation teaching analysis algorithm, a Bayesian model is constructed, and an adversarial neural network is built on its basis. Generate a translation teaching innovation model applicable to the translation teaching of university students. The translation teaching method is evaluated using the BLEU evaluation method. Experimental results: Both the correct translation rate of utterances based on the statistical computing method and dynamic memory algorithm reached 90%-95%. The traditional GLR translation teaching analysis algorithm achieved 95% correctness in recognizing declarative sentences, while the correctness rate for question and exclamation sentences was less than 95%. The correct translation rate of all the statements of the innovative model of translation teaching reached more than 97%. It can be seen that: The innovative model of translation teaching for college students with multimedia backgrounds is simpler and faster in calculation and more practical than other translation teaching algorithms, which is suitable for English translation work of college students and meets the proofreading needs of college students for translation teaching.

A systematic review on the effectiveness of children’s interactive reading applications for promoting their emergent literacy in the multimedia context

Emergent literacy is the term used to describe the reading and writing experiences of young children before they learn to write and read conventionally, and it is important for the construction of children’s early reading skills and the enhancement of their later reading performance. The systematic review was conducted to examine the effectiveness of children’s interactive reading apps in promoting emergent literacy for children between the ages of three and eight over the last decade (2013-2022). A total of 50 studies were included in this review, and it can be concluded that multimedia features (e.g., a dictionary, background music, and animated pictures) in children’s interactive reading apps are effective for enhancing emergent literacy. Conversely, interactive functions (such as games and hotspots) may distract children’s attention, leading to poor reading performances. This review also demonstrated the positive effects of children’s interactive reading apps on improving their learning outcomes and behavior. In addition, the results indicated that well-designed apps could promote children’s emerging literacy skills. However, more in-depth studies will be required in the future to provide designers with a well-defined guideline for designing reading apps for children.

Context-driven encrypted multimedia traffic classification on mobile devices

The Internet has been experiencing immense growth in multimedia traffic from mobile devices. The increase in traffic presents many challenges to user-centric networks, network operators, and service providers. Foremost among these challenges is the inability of networks to determine the types of encrypted traffic and thus the level of network service the traffic needs to maintain an acceptable quality of experience. Therefore, end devices are a natural fit for performing traffic classification since end devices have more contextual information about device usage and traffic. This paper proposes a novel approach that classifies multimedia traffic types produced and consumed on mobile devices. The technique relies on a mobile device’s detection of its multimedia context characterized by its utilization of different media input/output (I/O) components, e.g., camera, microphone, and speaker. We develop an algorithm, MediaSense, which senses the states of multiple I/O components and identifies the specific multimedia context of a mobile device in real-time. We demonstrate that MediaSense classifies encrypted multimedia traffic in real-time as accurately as deep learning approaches and with even better generalizability.

Construction of an Artificial Intelligence Writing Model for English Based on Fusion Neural Network Model.

This paper presents an in-depth study and analysis of the model of English writing using artificial intelligence algorithms of neural networks. Based on word vectors, the unsupervised disambiguation, and clustering of multimedia contexts extracted from massive online videos, the disambiguation accuracy reaches over 0.7, and the resulting small-scale multimedia context set can cover up to 90% of vocabulary learning tasks; user experiments show that the multimedia context learning system based on this method can improve the effectiveness and experience of ESL vocabulary learning, as well as the long-term word sense memory of learners. The results are 30% better. Based on the dependency grammatical relations and semantic metrics of collocations on a large-scale professional corpus, we established a collocation intention description and retrieval method in line with users' linguistic cognition and doubled the usage rate of collocation retrieval on the actual deployment system after half a year, becoming a user “sticky” ESL writing aid, and further defined style. Dictionaries only provide basic lexical definitions, and, even if supported by example sentences, they still cannot meet the needs of ESL authors in terms of expressive accuracy and richness. However, the current machine translation is based on the black box deep neural network construction, and its translation process is not understandable and interactive. Among the three algorithmic models constructed in this paper, the multitask learning model outperforms the conditional random field model and the LSTM-CRF model because the multitask learning model with auxiliary tasks solves the problem of sparse data to a certain extent, allowing the model to be trained more adequately in the case of uneven label distribution, and thus performs better than other models in the task of grammatical error detection.

Advantages and disadvantages of developing and producing educational multimedia content

The article discusses current trends in the field of distance education services. There are three main types of multimedia content, such as webinar, video lesson, and video conference. The main characteristics are disclosed in detail, as well as algorithms that must be followed during their development and production. The analysis of the proposed algorithms for the development and production of the specified multimedia content revealed a number of advantages and disadvantages inherent in each of the three types of content. In the order of discussion, new trends in the multimedia context were considered, such as webinar in the form of an interview, webinar (video lesson) in the form of a master class and networking. It is concluded that a qualitative and quantitative leap is now taking place in the field of educational services provided remotely.

ETHOS: a multi-label hate speech detection dataset

Online hate speech is a recent problem in our society that is rising at a steady pace by leveraging the vulnerabilities of the corresponding regimes that characterise most social media platforms. This phenomenon is primarily fostered by offensive comments, either during user interaction or in the form of a posted multimedia context. Nowadays, giant corporations own platforms where millions of users log in every day, and protection from exposure to similar phenomena appears to be necessary to comply with the corresponding legislation and maintain a high level of service quality. A robust and reliable system for detecting and preventing the uploading of relevant content will have a significant impact on our digitally interconnected society. Several aspects of our daily lives are undeniably linked to our social profiles, making us vulnerable to abusive behaviours. As a result, the lack of accurate hate speech detection mechanisms would severely degrade the overall user experience, although its erroneous operation would pose many ethical concerns. In this paper, we present ‘ETHOS’ (multi-labEl haTe speecH detectiOn dataSet), a textual dataset with two variants: binary and multi-label, based on YouTube and Reddit comments validated using the Figure-Eight crowdsourcing platform. Furthermore, we present the annotation protocol used to create this dataset: an active sampling procedure for balancing our data in relation to the various aspects defined. Our key assumption is that, even gaining a small amount of labelled data from such a time-consuming process, we can guarantee hate speech occurrences in the examined material.

Hesse's reader who no longer reads in the context of modern media

The article analyses several of Hesse's essays, with an emphasis on the 1920 essay On Reading Books, from the perspective of modern literary studies, psychology, and neuroscience. In the essay, Hesse made his classification of literary readers and anticipated the emergence of the "reader who no longer reads" as a kind of the enlightened reader, a human being who, thanks to his/her deep and dedicated understanding of emotions in literature, has the meaning of his/her life at his/her fingertips, who understands what he/she thinks and especially what he/she feels. Thus, it is the reader who really understands his/her emotions. However, nowadays, in the age of digital media, a new version of the "reader who does not read" is emerging. Such a reader is an arrogant and superficial modern reader who believes he/she knows everything only because he/she can easily reach information he/she does not even really try to understand, and who hardly thinks about emotions in literature. Therefore, the second part of the article relies on two more of Hesse's essays on reading literature, one of which anticipates the influence of multimedia on reading, and tries to explain the emergence of the modern "reader who does not read". More specifically, the article here considers the ways how literature can foster emotions and experience in the age of digital multimedia. Namely, if we want to feel and experience while reading literature, we need to develop both the cognitive and the emotional apparatus willing and able to understand what is read, but the modern media seem to stand in the way. It is good to point out the problem, but it is even better to offer the possibility of problem-solving; thus, the third part of the article addresses new/old knowledge about the effects of reading aloud on the development of our emotional and cognitive abilities. Of course, the methods of reading aloud in the multimedia context already exist, and they are successful, so the article also presents a study on stimulating emotions and empathy by the method of reading aloud.

Understanding consumer behavior in the multimedia context: incorporating gamification in VR-enhanced web system for tourism e-commerce.

This study aims to investigate how gamification and virtual reality (VR)-enhanced web services can be integrated to influence consumer behavior in the context of tourism e-commerce. A gamified VR-enhanced tourism web system (VRTWS) was designed and developed for this investigation, while a research framework with 12 hypotheses was proposed and empirically tested by adopting PLS-SEM approach to analyze 208 valid data collected from survey. The results reveal that both Enjoyment and Activation in Gamification significantly and positively affected Media Richness. Additionally, Media Richness significantly and positively affected both Usefulness and Ease of Use in using VR technology with gamification. Also, a user’s Perceived Value is not only positively affected by Usefulness and Ease of Use but also Interactivity and Immersion in a gamified VRTWS. Immersion was found to be positively affected by Presence. Through the positive effect on Satisfaction, user’s Perceived Value had positive effect on the Intention toward adoption. The proposed gamified VRTWS and the study results with implications are expected to be referenced by the researchers and practitioners for managing incorporation of gamification into designing, developing, and managing their VR-enhanced service in tourism e-commerce.

Lexical acquisition in a multi-media context

Lexical acquisition in a multi-media context

Entre síntoma y fármakon. La organología de la moral de Bernard Stiegler

Propósito/Contexto. Este artículo hace un recorrido por la filosofía de la técnica de Bernard Stiegler, con un enfoque en la dimensión moral de la perspectiva farmacológica. Su propósito está motivado por las cuestiones bioéticas que surgen de la perspectiva stiegleriana, en particular, por lo que concierne a los fenómenos de las adicciones a la tecnología digital y los efectos sociales y cognitivos que el contexto multimedia genera.
 Metodología/Enfoque. El enfoque metodológico que sustenta la elaboración de este artículo es la perspectiva farmacológica, elaborada por el propio Stiegler, por medio de la cual es posible replantear las bases de la ética y la moral en el contexto digital.
 Resultados/Hallazgos. El artículo hace una contribución teórica al debate sobre los efectos problemáticos y los beneficios de la adopción de la tecnología digital en todos los campos del saber y de las relaciones sociales, con un énfasis en los trastornos de la atención y los síntomas de malestar psicosocial.
 Discusión/Conclusiones/Contribuciones. Su contribución está en los elementos útiles que ofrece para un acercamiento metodológico entre la filosofía de la tecnología y la bioética (desde la farmacología y la organología). En este sentido, el trabajo de investigación y análisis del corpus stiegleriano se presenta como una aclaración de las apuestas bioéticas que conviven en la perspectiva farmacológica.

Integrative Research in Art and Science: A Framework for Proactive Humanities

ABSTRACT We argue that current cultural developments, driven by innovative technology, call for a reconsideration of the role of humanities as a field of study in which art and science is tightly integrated. This integration would allow the humanities to develop a proactive power such that it can (co-)steer the innovative developments of the techno-culture. Integrated art-science research may be realized in contexts where human expressive interaction with multimedia is investigated. Research outcomes from this domain may offer opportunities for humanities to contribute to cultural developments. Given the context of interactive multimedia, we offer a theoretical framework based on art-science research concerning: (1) human interaction, (2) interaction systems, and (3) cultural and societal interaction outcomes. The goal of the framework is to contribute to a new ambition for the humanities, one in which knowledge about culture, on top of being reflective, critical, and descriptive, has an intrinsic power to contribute to innovative techno-cultural developments.

Social Multimedia Security and Suspicious Activity Detection in SDN using Hybrid Deep Learning Technique

Social multimedia traffic is growing exponentially with the increased usage and continuous development of services and applications based on multimedia. Quality of Service (QoS), Quality of Information (QoI), scalability, reliability and such factors that are essential for social multimedia networks are realized by secure data transmission. For delivering actionable and timely insights in order to meet the growing demands of the user, multimedia analytics is performed by means of a trust-based paradigm. Efficient management and control of the network is facilitated by limiting certain capabilities such as energy-aware networking and runtime security in Software Defined Networks. In social multimedia context, suspicious flow detection is performed by a hybrid deep learning based anomaly detection scheme in order to enhance the SDN reliability. The entire process is divided into two modules namely – Abnormal activities detection using support vector machine based on Gradient descent and improved restricted Boltzmann machine which facilitates the anomaly detection module, and satisfying the strict requirements of QoS like low latency and high bandwidth in SDN using end-to-end data delivery module. In social multimedia, data delivery and anomaly detection services are essential in order to improve the efficiency and effectiveness of the system. For this purpose, we use benchmark datasets as well as real time evaluation to experimentally evaluate the proposed scheme. Detection of malicious events like confidential data collection, profile cloning and identity theft are performed to analyze the performance of the system using CMU-based insider threat dataset for large scale analysis.

Multimedia context interpretation: a semantics-based cooperative indexing approach

ABSTRACT The relative ineffectiveness of semantics-based multimedia indexing systems on the Web is caused by the semantic knowledge incompleteness and semantic heterogeneity problems. Nevertheless, the need to search multimedia documents with precision on the Web is persistently growing; pressing the demand for effective and efficient indexing strategies. In this article, we present an ontology-based multimedia indexing approach that cooperatively identifies the semantic and taxonomic relations that exist between annotation words that surround multimedia documents on Webpages. In this context, multiple ontologies are jointly employed for indexing each document. We construct inverted indexes in the form of semantic networks where nodes of each network are identified and added based on a majority-voting technique, while edges represent the semantic and taxonomic relations that hold between those nodes. To alleviate the heterogeneity between the resulting networks, we employ ontology merging algorithms to integrate them into consistent networks. We also utilise concept relatedness measures to enrich the networks with semantically-relevant entities that are not recognised by the used ontologies. To validate our proposal, we have developed a prototype system based on the proposed techniques. The produced results using real-world datasets demonstrate an improvement of the effectiveness against state-of-the-art baseline metrics.