Search results

1 – 10 of over 1000
Article
Publication date: 12 September 2023

Wei Shi, Jing Zhang and Shaoyi He

With the rapid development of short videos in China, the public has become accustomed to using short videos to express their opinions. This paper aims to solve problems such as…

100

Abstract

Purpose

With the rapid development of short videos in China, the public has become accustomed to using short videos to express their opinions. This paper aims to solve problems such as how to represent the features of different modalities and achieve effective cross-modal feature fusion when analyzing the multi-modal sentiment of Chinese short videos (CSVs).

Design/methodology/approach

This paper aims to propose a sentiment analysis model MSCNN-CPL-CAFF using multi-scale convolutional neural network and cross attention fusion mechanism to analyze the CSVs. The audio-visual and textual data of CSVs themed on “COVID-19, catering industry” are collected from CSV platform Douyin first, and then a comparative analysis is conducted with advanced baseline models.

Findings

The sample number of the weak negative and neutral sentiment is the largest, and the sample number of the positive and weak positive sentiment is relatively small, accounting for only about 11% of the total samples. The MSCNN-CPL-CAFF model has achieved the Acc-2, Acc-3 and F1 score of 85.01%, 74.16 and 84.84%, respectively, which outperforms the highest value of baseline methods in accuracy and achieves competitive computation speed.

Practical implications

This research offers some implications regarding the impact of COVID-19 on catering industry in China by focusing on multi-modal sentiment of CSVs. The methodology can be utilized to analyze the opinions of the general public on social media platform and to categorize them accordingly.

Originality/value

This paper presents a novel deep-learning multimodal sentiment analysis model, which provides a new perspective for public opinion research on the short video platform.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

Keywords

Open Access
Article
Publication date: 7 August 2023

Jijing Qian, Jialing Shang and Lianyi Qin

360-degree video is recorded with omnidirectional or multi-camera systems that capture all directions at the same time in a spherical view. With immersive technologies gaining…

Abstract

Purpose

360-degree video is recorded with omnidirectional or multi-camera systems that capture all directions at the same time in a spherical view. With immersive technologies gaining momentum and reducing educational cost, it has attracted the interest of the academic community. However, little is known about using 360-degree video in teacher education. The purpose of this study is to conduct a systematic scoping review through a systematic process based on 15 included studies to determine the characteristics, impacts, strengths and weaknesses of the 360-degree video applied to teacher education.

Design/methodology/approach

This study combines scoping and systematic review based on the PRISMA paradigm.

Findings

This paper explores that 360-degree videos are applicable to teacher education, specifically with their positive effects on pre-service teachers’ immersion, noticing, reflection and interpersonal competence. However, as for learners’ reactions, physical discomfort is reported, like motion sickness.

Research limitations/implications

First, some recently published studies on the subjects were partially accessible, which precluded the authors from adding their findings to this study. Second, the sample of articles is constrained to the search and selection strategies described in the methods section, which increases the possibility that pertinent research may be omitted. Furthermore, this study’s summary of the selected research may be inadequate. Third, only English-language publications were included in this study. Future researchers can expand on this topic by gathering additional relevant empirical data from publications in other languages.

Practical implications

Practically, findings in this study reveal the positive effects of 360-degree video in teacher education. The results may help researchers and preservice teachers better understand 360-degree video and use it more frequently in teaching. Instructional video technologies have been found to have a nearly medium effect on learning effectiveness in educational practice from a broader perspective.

Originality/value

The findings in this study can shed light on future educational technology research on instructional video technologies and technology-enhanced teacher education.

Details

Journal of Research in Innovative Teaching & Learning, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2397-7604

Keywords

Open Access
Article
Publication date: 22 September 2023

Linh Duong and Malin Brännback

This study aims to explore gender performance in entrepreneurial pitching. Understanding pitching as a social practice, the authors argue that pitch content and body gestures…

Abstract

Purpose

This study aims to explore gender performance in entrepreneurial pitching. Understanding pitching as a social practice, the authors argue that pitch content and body gestures contain gender-based norms and practices. The authors focus on early-stage ventures and the hegemonic masculinities and femininities that are performed in entrepreneurial pitches. The main research question is as follows: How is gender performed in entrepreneurial pitching?

Design/methodology/approach

The authors carried out the study with the post-structuralist feminist approach. The authors collected and analyzed nine online pitches with the reflexive thematic method to depict hegemonic masculinities and femininities performed at the pitch.

Findings

The authors found that heroic and breadwinner masculinities are dominant in pitching. Both male and female founders perform hegemonic masculinities. Entrepreneurs are expected to be assertive but empathetic people. Finally, there are connections between what entrepreneurs do and what investors ask, indicating the iteration of gender performance and expectations.

Research limitations/implications

While the online setting helps the authors to collect data during the pandemic, it limits the observation of the place, space and interactions between the judges/investors and the entrepreneurs. As a result, the linguistic and gesture communication of the investors in the pitch was not discussed in full-length in this paper. Also, as the authors observed, people would come to the pitch knowing what they should perform and how they should interact. Therefore, the preparation of the pitch as a study context could provide rich details on how gender norms and stereotypes influence people's interactions and their entrepreneurial identity. Lastly, the study has a methodological limitation. The authors did not include aspects of space in the analysis. It is mainly due to the variety of settings that the pitching sessions that the data set had.

Practical implications

For social practices and policies, the results indicate barriers to finance for women entrepreneurs. Women entrepreneurs are rewarded when they perform entrepreneurial hegemonic masculinities with a touch of emphasized femininities. Eventually, if women entrepreneurs do not perform correctly as investors expect them to, they will face barriers to acquiring finance. It is important to acknowledge how certain gendered biases might be (re)constructed and (re)produced through entrepreneurial activities, in which pitching is one of them.

Social implications

Practitioners could utilize research findings to understand how gender stereotypes exist not only on the pitch stage but also before and after the pitch, such as the choice of business idea and pitch training. In other words, it is necessary to create a more enabling environment for women entrepreneurs, such as customizing the accelerator program so that all business ideas receive relevant support from experts. On a macro level, the study has shown that seemingly gender-equal societies do not practically translate into higher participation of women in entrepreneurship.

Originality/value

For theoretical contributions, the study enhances the discussion that entrepreneurship is gendered; women and men entrepreneurs need to perform certain hegemonic traits to be legitimated as founders. The authors also address various pitching practices that shape pitch performance by including both textual and semiotic data in the study. This study provides social implications on the awareness of gendered norms and the design of entrepreneurial pitching.

Details

International Journal of Gender and Entrepreneurship, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1756-6266

Keywords

Article
Publication date: 14 December 2022

Priyabrata Mondal and Prabir Jana

Automation and the new buzzword, “Industry 4.0”, have dominated the media headlines in recent months. In this scenario, apparel manufacturers should not only install automatic…

Abstract

Purpose

Automation and the new buzzword, “Industry 4.0”, have dominated the media headlines in recent months. In this scenario, apparel manufacturers should not only install automatic machines but also standardise them based on specific industry requirements, and precise measures are required for daily target demands.

Design/methodology/approach

This study demonstrates the application of Predetermined Motion and Time System (PMTS) tools in various automatic and semiautomatic machines to obtain higher productivity and the highest utilisation percentage of operator and automats between the 1:1 and 1:2 man vs machine configuration models. In this study, timeSSD® was used to calculate the micro motions of humans. In addition, a video annotation and modelling software Tracker was used to calculate high-speed machine movements with loading frames of 30 FPS.

Findings

After the implementation of PMTS tools, it was found that for a 1:1 man vs machine configuration, the operator utilisation is 75% per shift and the operator idle time is 50% per cycle time, and the operator is sitting idle for 2 h per 8 h of shift. So, there is scope to improve the utilisation and idle time of operator.

Research limitations/implications

With the PMTS software, an industrial engineer professional with knowledge of the micromotion economy can only calculate micromotion.

Originality/value

Exploring the first time in the world to establish standard allowed minute (SAM) of a partly automated single-unit sewing machine with partial human intervention and a semiautomatic machine. Theoretical underpinnings indicate that manufacturers use the experience to determine the SAM of any operation over time, necessitating this work to calculate standard minutes automatically.

Article
Publication date: 21 December 2023

Vinit Kumar, Gopal Ji, Maya Deori and Manoj Kumar Verma

Vaccine hesitancy is a long-standing issue among both the general population and health communicators. This study aims to ascertain the inclination and the reasons for vaccine…

Abstract

Purpose

Vaccine hesitancy is a long-standing issue among both the general population and health communicators. This study aims to ascertain the inclination and the reasons for vaccine hesitancy by conducting content analysis and sentiment analysis of the perspectives expressed in comments on videos related to vaccine hesitancy uploaded from India on YouTube.

Design/methodology/approach

The assessment of the sentiments of the vaccine-hesitant population is done using Valence Aware Dictionary and sEntiment Reasoner sentiment analysis module implemented with Python’s NLTK library to automatically determine the sentiments of the comments. Manual content analysis was performed on 60.09% viewer comments randomly selected from the total comments in 238 videos on vaccine hesitancy originated from India and labelled each comment with labels “Anti”, “Pro”, “Confused”, “Not Applicable” and “Unrelated” labels.

Findings

The study found “Mistrust-Government policies”, “Fear-health related consequences”, “Mistrust-Scientific research”, “Vaccine effectiveness and efficacy” and “Misinformation/myths” as the top five determinants for vaccine hesitancy, whereas “Religious beliefs”, “Fear-Economic consequences”, “Side Effects- short-term” and “Fear-mode of administration” found to be the lesser cited reasons for vaccine hesitancy. However, the study also investigates changes in the inclination of Indian commenters towards vaccine hesitancy and revolving issues over time.

Social implications

Public health policymakers and health communicators may find the study useful in determining vaccine hesitancy factors in India.

Originality/value

The originality of this study lies in its approach. To date, no sentiment analysis has been conducted on the content released on YouTube by Indian content creators regarding pro- and anti-vaccination videos. This inquiry seeks to fill this research gap.

Details

Global Knowledge, Memory and Communication, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2514-9342

Keywords

Article
Publication date: 19 December 2023

Swagota Saikia, Vinit Kumar and Manoj Kumar Verma

The purpose of this study was to perform sentiment analysis and analyze the growth and popularity of Drupal, Joomla and WordPress on YouTube over a four-year period. This included…

Abstract

Purpose

The purpose of this study was to perform sentiment analysis and analyze the growth and popularity of Drupal, Joomla and WordPress on YouTube over a four-year period. This included identifying the most liked and commented videos for each content management system (CMS), ranking the CMSs based on the number of positive comments they received, and using natural language processing techniques to identify the top ten most frequently appearing words in videos about the CMSs.

Design/methodology/approach

The data for assessing the features of the videos of Drupal, WordPress and Joomla was extracted using Webometric Analyst version 4.4. with the help of the YouTube application programming interface key for videos on the selected CMSs uploaded from 2019 to 2022. The extraction of comments and sentiment analysis for the relevant videos was done using Mozdeh.

Findings

This study scrutinized 371, 234 and 313 videos of WordPress, Joomla and Drupal on YouTube. The findings reveal that there is a chronological growth of videos of the three CMSs in four years and till the present time, WordPress has the highest number of videos followed by Drupal and then Joomla. Regarding the ranking of highly liked videos, WordPress again wins the list with the highest number of likes in its videos followed by Drupal and then Joomla. For analyzing sentiments of the total comments extracted 123,409 for WordPress, 1,790 for Joomla and 1,783 for Drupal, respectively, WordPress receives the highest average positive comments followed by Drupal then Joomla. In top word frequency, the word “thank” highly occurs and viewers are asking for more tutorial videos.

Originality/value

To the best of the authors’ knowledge, this study is the first attempt for analyzing the sentiments of WordPress, Drupal and Joomla using Mozdeh software within the concerning period.

Details

Information Discovery and Delivery, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2398-6247

Keywords

Open Access
Article
Publication date: 22 August 2023

Mahesh Babu Purushothaman and Kasun Moolika Gedara

This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and…

1218

Abstract

Purpose

This pragmatic research paper aims to unravel the smart vision-based method (SVBM), an AI program to correlate the computer vision (recorded and live videos using mobile and embedded cameras) that aids in manual lifting human pose deduction, analysis and training in the construction sector.

Design/methodology/approach

Using a pragmatic approach combined with the literature review, this study discusses the SVBM. The research method includes a literature review followed by a pragmatic approach and lab validation of the acquired data. Adopting the practical approach, the authors of this article developed an SVBM, an AI program to correlate computer vision (recorded and live videos using mobile and embedded cameras).

Findings

Results show that SVBM observes the relevant events without additional attachments to the human body and compares them with the standard axis to identify abnormal postures using mobile and other cameras. Angles of critical nodal points are projected through human pose detection and calculating body part movement angles using a novel software program and mobile application. The SVBM demonstrates its ability to data capture and analysis in real-time and offline using videos recorded earlier and is validated for program coding and results repeatability.

Research limitations/implications

Literature review methodology limitations include not keeping in phase with the most updated field knowledge. This limitation is offset by choosing the range for literature review within the last two decades. This literature review may not have captured all published articles because the restriction of database access and search was based only on English. Also, the authors may have omitted fruitful articles hiding in a less popular journal. These limitations are acknowledged. The critical limitation is that the trust, privacy and psychological issues are not addressed in SVBM, which is recognised. However, the benefits of SVBM naturally offset this limitation to being adopted practically.

Practical implications

The theoretical and practical implications include customised and individualistic prediction and preventing most posture-related hazardous behaviours before a critical injury happens. The theoretical implications include mimicking the human pose and lab-based analysis without attaching sensors that naturally alter the working poses. SVBM would help researchers develop more accurate data and theoretical models close to actuals.

Social implications

By using SVBM, the possibility of early deduction and prevention of musculoskeletal disorders is high; the social implications include the benefits of being a healthier society and health concerned construction sector.

Originality/value

Human pose detection, especially joint angle calculation in a work environment, is crucial to early deduction of muscoloskeletal disorders. Conventional digital technology-based methods to detect pose flaws focus on location information from wearables and laboratory-controlled motion sensors. For the first time, this paper presents novel computer vision (recorded and live videos using mobile and embedded cameras) and digital image-related deep learning methods without attachment to the human body for manual handling pose deduction and analysis of angles, neckline and torso line in an actual construction work environment.

Details

Smart and Sustainable Built Environment, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2046-6099

Keywords

Article
Publication date: 18 October 2021

Anilkumar Chandrashekhar Korishetti and Virendra S. Malemath

High-efficiency video coding (HEVC) is the latest video coding standard that has better coding efficiency than the H.264/advanced video coding (AVC) standard. The purpose of this…

Abstract

Purpose

High-efficiency video coding (HEVC) is the latest video coding standard that has better coding efficiency than the H.264/advanced video coding (AVC) standard. The purpose of this paper is to design and develop an effective block search mechanism for the video compression-HEVC standard such that the developed compression standard is applied for the communication applications.

Design/methodology/approach

In the proposed method, an rate-distortion (RD) trade-off, named regressive RD trade-off is used based on the conditional autoregressive value at risk (CaViar) model. The motion estimation (ME) is based on the new block search mechanism, which is developed with the modification in the Ordered Tree-based Hex-Octagon (OrTHO)-search algorithm along with the chronological Salp swarm algorithm (SSA) based on deep recurrent neural network (deepRNN) for optimally deciding the shape of search, search length of the tree and dimension. The chronological SSA is developed by integrating the chronological concept in SSA, which is used for training the deep RNN for ME.

Findings

The competing methods used for the comparative analysis of the proposed OrTHO-search based RD + chronological-salp swarm algorithm (RD + C-SSA) based deep RNN are support vector machine (SVM), fast encoding framework, wavefront-based high parallel (WHP) and OrTHO-search based RD method. The proposed video compression method obtained a maximum peak signal-to-noise ratio (PSNR) of 42.9180 dB and a maximum structural similarity index measure (SSIM) of 0.9827.

Originality/value

In this research, an effective block search mechanism was developed with the modification in the OrTHO-search algorithm along with the chronological SSA based on deepRNN for the video compression-HEVC standard.

Details

Journal of Engineering, Design and Technology , vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1726-0531

Keywords

Article
Publication date: 5 October 2023

Sheng Yuan

The purpose of this study is to compare the communication practices of Chinese and US companies on YouTube and explores the effectiveness of different communication strategies at…

Abstract

Purpose

The purpose of this study is to compare the communication practices of Chinese and US companies on YouTube and explores the effectiveness of different communication strategies at the topic level.

Design/methodology/approach

The author selected 22 Chinese companies and 22 US firms and compared the content of their English language corporate YouTube channels through content analysis, sentiment analysis and cluster analysis.

Findings

The results revealed that the three communication strategies (information, response and involvement) in general were not significantly different regarding their engagement rates, but they generated different comment scores when communicating topics of corporate social responsibility. The results also showed that Chinese companies were more likely than American firms to display the speeches of corporate leaders, use collectivistic references and present human interest messages in YouTube videos.

Research limitations/implications

This study sheds light on how national institutional environment shapes corporate communication on YouTube.

Practical implications

This study challenges the infatuation with the involvement strategy and offers some advice for practitioners on topic selection and user comment function management.

Originality/value

This study makes a novel contribution to the literature of corporate communication on YouTube by adopting a cross-national comparative approach. A conceptual framework of major factors influencing stakeholder responses on YouTube was presented.

Peer review

The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-02-2023-0061

Details

Online Information Review, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 1468-4527

Keywords

Article
Publication date: 25 January 2024

Yaolin Zhou, Zhaoyang Zhang, Xiaoyu Wang, Quanzheng Sheng and Rongying Zhao

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned…

Abstract

Purpose

The digitalization of archival management has rapidly developed with the maturation of digital technology. With data's exponential growth, archival resources have transitioned from single modalities, such as text, images, audio and video, to integrated multimodal forms. This paper identifies key trends, gaps and areas of focus in the field. Furthermore, it proposes a theoretical organizational framework based on deep learning to address the challenges of managing archives in the era of big data.

Design/methodology/approach

Via a comprehensive systematic literature review, the authors investigate the field of multimodal archive resource organization and the application of deep learning techniques in archive organization. A systematic search and filtering process is conducted to identify relevant articles, which are then summarized, discussed and analyzed to provide a comprehensive understanding of existing literature.

Findings

The authors' findings reveal that most research on multimodal archive resources predominantly focuses on aspects related to storage, management and retrieval. Furthermore, the utilization of deep learning techniques in image archive retrieval is increasing, highlighting their potential for enhancing image archive organization practices; however, practical research and implementation remain scarce. The review also underscores gaps in the literature, emphasizing the need for more practical case studies and the application of theoretical concepts in real-world scenarios. In response to these insights, the authors' study proposes an innovative deep learning-based organizational framework. This proposed framework is designed to navigate the complexities inherent in managing multimodal archive resources, representing a significant stride toward more efficient and effective archival practices.

Originality/value

This study comprehensively reviews the existing literature on multimodal archive resources organization. Additionally, a theoretical organizational framework based on deep learning is proposed, offering a novel perspective and solution for further advancements in the field. These insights contribute theoretically and practically, providing valuable knowledge for researchers, practitioners and archivists involved in organizing multimodal archive resources.

Details

Aslib Journal of Information Management, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 2050-3806

Keywords

1 – 10 of over 1000