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1.
《Information processing & management》2023,60(3):103254
Viewer gifting is an important business mode in live streaming industry, which closely relates to the income of the platforms and streamers. Previous studies on gifting prediction are often limited to cross-section data and consider the problem from the macro perspective of the whole live streaming. However, the multimodal information and the time accumulation effect of live streaming content on viewer gifting behavior are ignored. In this paper, we put forward a multimodal time-series method (MTM) for predicting real-time gifting. The core module of the method is the multimodal time-series analysis (MTA), which targets at effectively fusing multimodal information. Specifically, the proposed orthogonal projection (OP) model can promote cross-modal information interaction without introducing additional parameters. To achieve the interaction of multi-modal information at the same level, we also design a stackable joint representation layer, which makes each target modality's representation (visual, acoustic and textual modality) can benefit from all the other modalities. The residual connections are introduced as well to ensure the integration of low-level and high-level information. On our dataset, our model shows improved performance compared to other advanced models by at least 8% on F1. Meanwhile, the MTA is able to meet the real-time requirements of the live streaming setting, and has demonstrated its robustness and transferability in other tasks. Our research may offer some insights about how to efficiently fuse multimodal information, and contribute to the research on viewer gifting behavior prediction in the live streaming context. 相似文献
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Yemen has witnessed decades of political unrest and the current armed conflict has significantly impacted human development. The economic activity has been severely disrupted which in turn affected the delivery of public services including the financing and operation of the higher education system (HE), where efficiency was negatively impacted.The purpose of this research is to investigate the extent of which the internal efficiency of the Yemen HE has been affected. This will be achieved through analysing the main three domains of teaching and learning activities as well as the impacts of the adopted policies by HE management. Structured interviews with standardized closed-ended and open-ended questions were conducted online with 51 academics who have been purposely selected. Despite the devastating effects of the armed conflict, the HE has continued to perform its duties, providing space for learning and contributing effectively in social cohesion. Nonetheless, the education process has been impacted quantitatively and qualitatively.Yemen has been deprived of its well-qualified human capital, and the brain-drain is still ongoing. The continuity of conflict will yield a generation who is either uneducated or poorly educated, and this will in turn continue feeding the violence and jeopardizing Yemen’s future.This paper represents a first attempt to study the effects of Yemen’s armed conflict on HE. Future research should shed light on tracing students who abandoned education as well as the level of knowledge, skills and competencies of those lately graduated. The multi-dimensional effects of brain-drain are equally important. 相似文献
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《Information processing & management》2023,60(3):103271
Because of the rapid increase of data in the cloud of Amazon Web Service (AWS), the traditional methods for analyzing this data are not good and inappropriate, so unconventional methods of analysis have been proposed by many data scientists such as concurrent/ parallel techniques to meeting the requirements of performance and scalability entailed in such big data analyses. In this paper we are used Hadoop Map Reduce system that contains Hadoop Distributed File System (HDFS) and Hadoop cluster. We optimized it by combining it with five efficient Data Mining (DM) algorithms such as Support Vector Machine (SVM), Decision Tree (DT), Random Forest (RF), Correlative Naïve Bayes classifier (CNB), and Fuzzy CNB (FCNB) for strong analytics of cloud big data. The proposed system applied on product review data that taken form the cloud of AWS. The Evaluation of Hadoop Map Reduce done with important benchmarks as Mean Absolute Percentage Error (MPAE), Root Mean Square Error (RMSE), and runtime for word count, sort, inverted index. Also, the evaluation of DM models with Hadoop Map Reduce system done by using accuracy, sensitivity, specificity, memory, and running time. Experiments have shown that FCNB is effective in addressing the problem of big data. 相似文献
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This paper reports on a case study involving a strategic and innovative approach to creation of an in-house multifaceted digital engineering platform (the DEP) in overcoming a number of organisational problems at a multinational engineering company. The DEP was to be used strategically for simplifying the operational complexity and to create and appropriate new work-related mind-set and new organisational discourse to achieve homogenous working across the organisation, which is a huge challenge. The need for this system emerged from the need to resolve many organisational services related problems that carried phenomenal amount of processes, health and safety risks and to regulate, and, control the running of engineering project. Research data were collected using a longitudinal case study approach over a period of six months. In order to make sense of how the DEP helped the organisation, the study used certain elements of Extended Structuration Theory as a lens to assess the case study. This research discovered that the DEP succeeded in creating and appropriating work-related mind-set and organisational discourse. It also had real influence on working processes and employees at all levels while encouraging transparency, responsiveness, agility and accountability. It continues to help the organisation to govern, manage and maintain good standard of service but many barriers still remain. 相似文献
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In social networking services (SNSs), users’ unclear understanding of the large and invisible audience increases the chances of online turbulence, which is a key source of SNS-induced stress. This growing phenomenon has gained increasing attention in academia and industry due to the undesirable consequences for users and SNS platforms. In this study, we draw from the transactional model of stress to examine how audience management strategies impact online turbulence and lead to neglected unintended audience concern and lurking. We also investigate the role of self-monitoring as a stress inhibitor. We test our model with data collected from 301 SNS users. The results show that the four types of audience management strategies have different effects on online turbulence, which significantly impacts neglected unintended audience concern especially when users have high self-monitoring skills. We believe that this work contributes, both from scientific and practical standpoints, to the understanding of the interventions and stressful responses of online turbulence in SNSs. 相似文献
8.
Extant research on technology acceptance has devoted considerable attention to the relationship between behavioral intention (BI) and system use (SU) over time. However, the empirical results have been mixed—studies have found BI to both influence and not influence SU. Studies that examined the BI→SU relationship have employed different research models and research designs. Prior research models have examined direct effects on SU, indirect effects on SU through BI, the moderator effects on BI→SU, and the mediating role of BI in BI→SU. Studies have employed different types of respondents, information technologies, geographic regions, voluntariness, and measurement designs. This study proposes that such differences in research models and designs contribute to the mixed results for BI→SU, and reports a meta-analysis of findings reported in 113 prior studies along with a critical review of the BI→SU relationship. While no significant differences were found in the results for the BI→SU relationship across various research design characteristics, this study finds that the measurement of SU has been conflated with future and current or past behavior, direct and indirect effects on SU impact BI→SU, BI is modeled to fully and partially mediate the effects of other variables on SU, and moderators for the BI→SU relationship may be necessary. This study identifies several directions for future research and underlines the need to rethink the link between BI and SU. 相似文献
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Most studies on O2O services have focused solely on the technological merits of mobile applications, overlooking the role of the value systems that underlie people’s lifestyles.In contrast, this research sheds light on how people’s value systems influence their decision to adopt food delivery applications. Particularly, it proposes that people’s moral obligation in meal preparation can change the mode of thinking that guides their adoption decision. Namely, moral obligation is assumed to restrict people from acting on their basic convenience orientation in meal preparation. Empirical results have supported this assumption by showing that people with a high moral obligation (or married people) are more reluctant to convert their basic convenience-seeking tendencies into actual adoption intention than those with a low moral obligation (or single people). The important theoretical and managerial implications of these results are also discussed. 相似文献