Journal on Multimodal User Interfaces

Top Research Topics at Journal on Multimodal User Interfaces?

Journal on Multimodal User Interfaces focuses largely on the fields of Human–computer interaction, Artificial intelligence, Multimedia, Speech recognition and Gesture. The journal focuses on Human–computer interaction but the discussions also offer insight into other areas such as Context (language use) and Haptic technology. Topics in Artificial intelligence explored in it were investigated in conjunction with research in Machine learning, Pattern recognition, Computer vision and Natural language processing.

The Multimedia works featured in it incorporate elements from User experience design and Mobile device. While work presented in the journal provided substantial information on Speech recognition, it also covered topics in Modality (human–computer interaction) and Perception. Gesture recognition is a focus of the presented Gesture works and it dives deep in Gesture recognition.

The journal explores research in Facial expression and the adjacent study of Affective computing.

• Human–computer interaction (43.39%)
• Artificial intelligence (25.66%)
• Multimedia (18.52%)

What are the most cited papers published in the journal?

• EmoNets: Multimodal deep learning approaches for emotion recognition in video (234 citations)
• Hierarchical committee of deep convolutional neural networks for robust facial expression recognition (151 citations)
• Multimodal emotion recognition in speech-based interaction using facial expression, body gesture and acoustic analysis (146 citations)

Research areas of the most cited articles at Journal on Multimodal User Interfaces:

The most cited papers cover a variety of subjects, including Artificial intelligence, Human–computer interaction, Speech recognition, Multimedia and Gesture. While work presented in the journal publications provide substantial information on Artificial intelligence, it also covers topics in Machine learning, Computer vision and Natural language processing. The majority of Human–computer interaction studies presented in the most cited publications zero in on Multimodal interaction.

What topics the last edition of the journal is best known for?

• Artificial intelligence
• Machine learning
• The Internet

The previous edition focused in particular on these issues:

The discussions in the journal mainly cover the fields of Human–computer interaction, Perception, Usability, Artificial intelligence and Sonification. Robot, Gesture, Eye tracking and Gaze are some topics wherein Human–computer interaction research discussed in it have an impact. The overlapping concepts between Touchscreen and Wearable computer, Modality (human–computer interaction) and Braille are the key highlights of Gesture study.

Perception research presented in it encompasses a variety of subjects, including Context (language use), Ultimatum game, Information processing and Priming (psychology). It holds forums on Usability that merges themes from other disciplines such as User experience design, Video game and Public speaking anxiety. The research on Artificial intelligence tackled can also make contributions to studies in the areas of Machine learning and Pattern recognition.

The most cited articles from the last journal are:

• “Let me explain!”: exploring the potential of virtual agents in explainable AI interaction design (9 citations)
• A BCI video game using neurofeedback improves the attention of children with autism (6 citations)
• Comparing mind perception in strategic exchanges: human-agent negotiation, dictator and ultimatum games (3 citations)

Papers citation over time

A key indicator for each journal is its effectiveness in reaching other researchers with the papers published at that venue.

The chart below presents the interquartile range (first quartile 25%, median 50% and third quartile 75%) of the number of citations of articles over time.

Top authors and change over time

The top authors publishing in Journal on Multimodal User Interfaces (based on the number of publications) are:

• Dirk Heylen (10 papers) absent at the last edition,
• Marc Leman (7 papers) published 2 papers at the last edition,
• Antonio Camurri (7 papers) absent at the last edition,
• Albert Ali Salah (6 papers) published 2 papers at the last edition,
• Roberto Bresin (6 papers) absent at the last edition.

The overall trend for top authors publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top authors.

Top affiliations and change over time

Only papers with recognized affiliations are considered

The top affiliations publishing in Journal on Multimodal User Interfaces (based on the number of publications) are:

• University of Twente (17 papers) absent at the last edition,
• Royal Institute of Technology (12 papers) published 1 paper at the last edition,
• Queen Mary University of London (9 papers) published 1 paper at the last edition,
• Boğaziçi University (9 papers) published 2 papers at the last edition,
• Centre national de la recherche scientifique (8 papers) absent at the last edition.

The overall trend for top affiliations publishing in this journal is outlined below. The chart shows the number of publications at each edition of the journal for top affiliations.

Publication chance based on affiliation

The publication chance index shows the ratio of articles published by the best research institutions in the journal edition to all articles published within that journal. The best research institutions were selected based on the largest number of articles published during all editions of the journal.

The chart below presents the percentage ratio of articles from top institutions (based on their ranking of total papers).Top affiliations were grouped by their rank into the following tiers: top 1-10, top 11-20, top 21-50, and top 51+. Only articles with a recognized affiliation are considered.

During the most recent 2021 edition, 9.09% of publications had an unrecognized affiliation. Out of the publications with recognized affiliations, 15.00% were posted by at least one author from the top 10 institutions publishing in the journal. Another 5.00% included authors affiliated with research institutions from the top 11-20 affiliations. Institutions from the 21-50 range included 17.50% of all publications and 62.50% were from other institutions.

Returning Authors Index

A very common phenomenon observed among researchers publishing scientific articles is the intentional selection of journals they have already attended in the past. In particular, it is worth analyzing the case when the authors participate in the same journal from year to year.

The Returning Authors Index presented below illustrates the ratio of authors who participated in both a given as well as the previous edition of the journal in relation to all participants in a given year.

Returning Institution Index

The graph below shows the Returning Institution Index, illustrating the ratio of institutions that participated in both a given and the previous edition of the conference in relation to all affiliations present in a given year.

The experience to innovation index

Our experience to innovation index was created to show a cross-section of the experience level of authors publishing in a journal. The index includes the authors publishing at the last edition of a journal, grouped by total number of publications throughout their academic career (P) and the total number of citations of these publications ever received (C).

The group intervals were selected empirically to best show the diversity of the authors' experiences, their labels were selected as a convenience, not as judgment. The authors were divided into the following groups:

• Novice - P < 5 or C < 25 (the number of publications less than 5 or the number of citations less than 25),
• Competent - P < 10 or C < 100 (the number of publications less than 10 or the number of citations less than 100),
• Experienced - P < 25 or C < 625 (the number of publications less than 25 or the number of citations less than 625),
• Master - P < 50 or C < 2500 (the number of publications less than 50 or the number of citations less than 2500),
• Star - P ≥ 50 and C ≥ 2500 (both the number of publications greater than 50 and the number of citations greater than 2500).

The chart below illustrates experience levels of first authors in cases of publications with multiple authors.

Career Opportunities in the Field of Multimodal User Interfaces

Understanding the subjects, methods, and applications discussed in the Journal on Multimodal User Interfaces not only broadens one's theoretical knowledge but also provides insights into practical aspects and career opportunities. This knowledge can be used to pursue various job profiles in different sectors from academia to high-tech enterprises. For instance, major advancements and research areas like Gesture Recognition could lead to positions as Gesture Recognition Engineers or Software Developers in tech firms working on developing new interfaces for computing devices. Similarly, study fields such as Artificial Intelligence and Machine Learning open up countless opportunities in AI research, data analysis, and intelligent systems design. In the educational sector, one could explore options as a preschool teacher assistant. A role of preschool teacher assistant requires understanding of human-computer interaction, perception, and cognitive development, all of which are key elements studied in this Journal. To understand more about the role of a preschool teacher assistant, including job responsibilities and potential earnings, you can find more details at our career guidance corner here to gather information about preschool teacher assistant salary in New York. The takeaway here is that being familiar with the topics discussed in the Journal on Multimodal User Interfaces could be a stepping stone towards a promising career path in the intersection of technology and human interaction development.