Search results
1 – 10 of 155Ziming Zeng, Tingting Li, Shouqiang Sun, Jingjing Sun and Jie Yin
Twitter fake accounts refer to bot accounts created by third-party organizations to influence public opinion, commercial propaganda or impersonate others. The effective…
Abstract
Purpose
Twitter fake accounts refer to bot accounts created by third-party organizations to influence public opinion, commercial propaganda or impersonate others. The effective identification of bot accounts is conducive to accurately judge the disseminated information for the public. However, in actual fake account identification, it is expensive and inefficient to manually label Twitter accounts, and the labeled data are usually unbalanced in classes. To this end, the authors propose a novel framework to solve these problems.
Design/methodology/approach
In the proposed framework, the authors introduce the concept of semi-supervised self-training learning and apply it to the real Twitter account data set from Kaggle. Specifically, the authors first train the classifier in the initial small amount of labeled account data, then use the trained classifier to automatically label large-scale unlabeled account data. Next, iteratively select high confidence instances from unlabeled data to expand the labeled data. Finally, an expanded Twitter account training set is obtained. It is worth mentioning that the resampling technique is integrated into the self-training process, and the data class is balanced at the initial stage of the self-training iteration.
Findings
The proposed framework effectively improves labeling efficiency and reduces the influence of class imbalance. It shows excellent identification results on 6 different base classifiers, especially for the initial small-scale labeled Twitter accounts.
Originality/value
This paper provides novel insights in identifying Twitter fake accounts. First, the authors take the lead in introducing a self-training method to automatically label Twitter accounts from the semi-supervised background. Second, the resampling technique is integrated into the self-training process to effectively reduce the influence of class imbalance on the identification effect.
Details
Keywords
Jingjing Sun, Ziming Zeng, Tingting Li and Shouqiang Sun
The outbreak of COVID-19 has become a major public health emergency worldwide. How to effectively guide public opinion and implement precise prevention and control is a hot topic…
Abstract
Purpose
The outbreak of COVID-19 has become a major public health emergency worldwide. How to effectively guide public opinion and implement precise prevention and control is a hot topic in current research. Mining the spatiotemporal coupling between online public opinion and offline epidemics can provide decision support for the precise management and control of future emergencies.
Design/methodology/approach
This study focuses on analyzing the spatiotemporal coupling relationship between public opinion and the epidemic. First, based on Weibo information and confirmed case information, a field framework is constructed using field theory. Second, SnowNLP is used for sentiment mining and LDA is utilized for topic extraction to analyze the topic evolution and the sentiment evolution of public opinion in each coupling stage. Finally, the spatial model is used to explore the coupling relationship between public opinion and the epidemic in space.
Findings
The findings show that there is a certain coupling between online public opinion sentiment and offline epidemics, with a significant coupling relationship in the time dimension, while there is no remarkable coupling relationship in space. In addition, the core topics of public concern are different at different coupling stages.
Originality/value
This study deeply explores the spatiotemporal coupling relationship between online public opinion and offline epidemics, adding a new research perspective to related research. The result can help the government and relevant departments understand the dynamic development of epidemic events and achieve precise control while mastering the dynamics of online public opinion.
Details
Keywords
Jingjing Sun, Tingting Li and Shouqiang Sun
This paper aims to investigate how online consumer reviews (OCRs), countdowns and self-control affect consumers' online impulse buying behavior in online group buying (OGB) and…
Abstract
Purpose
This paper aims to investigate how online consumer reviews (OCRs), countdowns and self-control affect consumers' online impulse buying behavior in online group buying (OGB) and uncover the relationship between these factors.
Design/methodology/approach
Based on the stimulus-organism-response (SOR) framework, this research examines the effects of OCRs, countdowns and self-control on users' impulse purchases. First, the influence of emotions on impulse purchases in group purchasing is investigated. In addition, this study innovatively applies stress-coping theory to group buying research, with countdowns exerting temporal pressure on consumers and OCRs viewed as social pressure, to investigate in depth how countdowns and OCRs affect users' impulse purchase behavior. Finally, this study also surveys the moderating role of users' self-control in the impulse purchase process.
Findings
The results show that the perceived value of OCRs and positive emotions (PE) were positively correlated with impulsiveness (IMP) and the urge to buy impulsively (UBI), while negative emotions (NE) were negatively correlated with IMP. Countdowns (CD) had a positive effect on UBI. Self-control can indirectly affect users' impulse buying by negatively moderating the relationship between PE and UBI, PE and IMP and CD and UBI.
Originality/value
The research results can help group buying platforms and related participants understand the factors influencing users' impulse purchases in OGB and facilitate them to better design strategies to increase product sales.
Details
Keywords
Tingting Li, Ziming Zeng, Jingjing Sun and Shouqiang Sun
The deployment of vaccines is the primary task in curbing the COVID-19 pandemic. The purpose of this paper is to understand the public’s opinions on vaccines and then design…
Abstract
Purpose
The deployment of vaccines is the primary task in curbing the COVID-19 pandemic. The purpose of this paper is to understand the public’s opinions on vaccines and then design effective interventions to promote vaccination coverage.
Design/methodology/approach
This paper proposes a research framework based on the spatiotemporal perspective to analyse the public opinion evolution towards COVID-19 vaccine in China. The framework first obtains data through crawler tools. Then, with the help of data mining technologies, such as emotion computing and topic extraction, the evolution characteristics of discussion volume, emotions and topics are explored from spatiotemporal perspectives.
Findings
In the temporal perspective, the public emotion declines in the later stage, but overall emotion performance is positive and stabilizing. This decline in emotion is mainly associated with ambiguous information about the COVID-19 vaccine. The research progress of vaccines and the schedule of vaccination have driven the evolution of public discussion topics. In the spatial perspective, the public emotion tends to be positive in 31 regions, whereas local emotion increases and decreases in different stages. The dissemination of distinctive information and the local epidemic prevention and control status may be potential drivers of topic evolution in local regions.
Originality/value
The analysis results of media information can assist decision-makers to accurately grasp the subjective thoughts and emotional expressions of the public in terms of spatiotemporal perspective and provide decision support for macro-control response strategies and risk communication.
Details
Keywords
Ziming Zeng, Shouqiang Sun, Tingting Li, Jie Yin and Yueyan Shen
The purpose of this paper is to build a mobile visual search service system for the protection of Dunhuang cultural heritage in the smart library. A novel mobile visual search…
Abstract
Purpose
The purpose of this paper is to build a mobile visual search service system for the protection of Dunhuang cultural heritage in the smart library. A novel mobile visual search model for Dunhuang murals is proposed to help users acquire rich knowledge and services conveniently.
Design/methodology/approach
First, local and global features of images are extracted, and the visual dictionary is generated by the k-means clustering. Second, the mobile visual search model based on the bag-of-words (BOW) and multiple semantic associations is constructed. Third, the mobile visual search service system of the smart library is designed in the cloud environment. Furthermore, Dunhuang mural images are collected to verify this model.
Findings
The findings reveal that the BOW_SIFT_HSV_MSA model has better search performance for Dunhuang mural images when the scale-invariant feature transform (SIFT) and the hue, saturation and value (HSV) are used to extract local and global features of the images. Compared with different methods, this model is the most effective way to search images with the semantic association in the topic, time and space dimensions.
Research limitations/implications
Dunhuang mural image set is a part of the vast resources stored in the smart library, and the fine-grained semantic labels could be applied to meet diverse search needs.
Originality/value
The mobile visual search service system is constructed to provide users with Dunhuang cultural services in the smart library. A novel mobile visual search model based on BOW and multiple semantic associations is proposed. This study can also provide references for the protection and utilization of other cultural heritages.
Details
Keywords
Qun Bai, Senming Tan, Zheng Yuelong, Jiafu Su and Li Tingting
This study investigates the credit supervision issue in rural e-commerce. By studying the trading strategies of buyers and sellers under different credit supervision measures and…
Abstract
Purpose
This study investigates the credit supervision issue in rural e-commerce. By studying the trading strategies of buyers and sellers under different credit supervision measures and the impact of different pricing strategies on the trading strategies of both parties, this paper proposes regulatory suggestions for the increasingly severe credit problems in rural e-commerce.
Design/methodology/approach
In the online agricultural product transaction between farmers and consumers, both parties' decision-making is a dynamic process. Using the copying dynamic model of the evolutionary game, this study establishes two evolutionary game models to explore the factors affecting credit supervision in the rural e-commerce transaction process. Then, the study provides corresponding countermeasures and suggestions.
Findings
First, credit supervision measures implemented by rural e-commerce platforms and the Government's legal system construction and infrastructure construction guarantees influence both parties' trust choices in rural e-commerce transactions. Second, price is a key factor affecting both parties' trading strategies. In the case of relatively fair prices, the higher the proportion of farmers who choose “low price” and “honest transaction” strategies, the easier that is for consumers to choose to trust farmers. In contrast, the higher the price, the higher the proportion of consumers who choose the “trust farmers” strategy, and the more willing farmers are to choose honest transactions.
Originality/value
This work develops a new approach for analyzing rural e-commerce credit supervision. Moreover, this study helps establish and improve the credit supervision mechanism of rural e-commerce and further realize the long-term sustainable development of the rural economy.
Details
Keywords
Lijun Dong, Naichao Chen, Jiawen Liang, Tingting Li, Zhanlin Yan and Bing Zhang
The purpose of this study is to provide an in-depth understanding about the indoor-orbital electrical inspection robot, which is useful for motivating the further investigation on…
Abstract
Purpose
The purpose of this study is to provide an in-depth understanding about the indoor-orbital electrical inspection robot, which is useful for motivating the further investigation on the inspection of electrical equipment. Currently, electric energy has a strong correlation with the economic development of the country. Intelligent substations play an important role in the transmission and distribution of the electricity; the maintenance of the substation has attracted intensive attention due to the requirement of reliability and safety. The indoor-orbital electrical inspection robot has increasingly become the main tool to realize the unmanned. Hence, a systematic review is conducted systematically reviewing the current technical status of the indoor-orbital electrical inspection robot and discuss the existed problems.
Design/methodology/approach
In this paper, the most essential achievements in the field of indoor-orbital electrical inspection robots were reported to present the current status, and the mechanical structures and key inspective technologies were also discussed.
Findings
Four recommendations are provided from the analyzed review, which have made constructive comments on the overall structural design, functionality, intelligence and future development direction of the indoor-orbital electrical inspection robot, respectively.
Originality/value
To the best of the authors’ knowledge, this is the first systematic review study on indoor-orbital electrical inspection robots; it fills the theoretical gap and proffers design ideas and directions for the development of the indoor-orbital electrical inspection robot.
Details
Keywords
Tingting Li, Mohd Zamre Mohd Zahir and Hasani Mohd Ali
This study aims to make some contribution to the process of corporate compliance governance in China.
Abstract
Purpose
This study aims to make some contribution to the process of corporate compliance governance in China.
Design/methodology/approach
This paper adopts qualitative method, literature research, case analysis and comparative methods to explore the Chinese compliance governance model in the field of collusive bidding crimes.
Findings
In the process of criminal prosecution of enterprises suspected of committing crimes, the judicial authorities should promote the restoration of normal production and operation of corporate enterprises by promoting the construction of corporate compliance, which is conducive to solving the difficult problem of attribution of collusive bidding crimes. In addition, corporate compliance under prosecutorial supervision is also conducive to optimizing the regulatory path of collusive bidding and achieving more effective prevention and control of unit crimes in the mode of co-regulation between the state and corporate.
Originality/value
Compliance governance corporate crime is at a nascent stage in China, and this study seeks to provide some reference for future compliance review governance in China through the analysis of specific business crime cases.
Details
Keywords
Ziming Zeng, Tingting Li, Jingjing Sun, Shouqiang Sun and Yu Zhang
The proliferation of bots in social networks has profoundly affected the interactions of legitimate users. Detecting and rejecting these unwelcome bots has become part of the…
Abstract
Purpose
The proliferation of bots in social networks has profoundly affected the interactions of legitimate users. Detecting and rejecting these unwelcome bots has become part of the collective Internet agenda. Unfortunately, as bot creators use more sophisticated approaches to avoid being discovered, it has become increasingly difficult to distinguish social bots from legitimate users. Therefore, this paper proposes a novel social bot detection mechanism to adapt to new and different kinds of bots.
Design/methodology/approach
This paper proposes a research framework to enhance the generalization of social bot detection from two dimensions: feature extraction and detection approaches. First, 36 features are extracted from four views for social bot detection. Then, this paper analyzes the feature contribution in different kinds of social bots, and the features with stronger generalization are proposed. Finally, this paper introduces outlier detection approaches to enhance the ever-changing social bot detection.
Findings
The experimental results show that the more important features can be more effectively generalized to different social bot detection tasks. Compared with the traditional binary-class classifier, the proposed outlier detection approaches can better adapt to the ever-changing social bots with a performance of 89.23 per cent measured using the F1 score.
Originality/value
Based on the visual interpretation of the feature contribution, the features with stronger generalization in different detection tasks are found. The outlier detection approaches are first introduced to enhance the detection of ever-changing social bots.
Details
Keywords
Zelin Tong, Tingting Li, Wenting Feng, Yuanyuan Zhou and Ling Zhou
This study aims to investigate the impact of cross-border charitable activities on host- and home-country consumers based on the social identity theory.
Abstract
Purpose
This study aims to investigate the impact of cross-border charitable activities on host- and home-country consumers based on the social identity theory.
Design/methodology/approach
Through an extensive literature review and two experimental designs, this study establishes the research framework and hypothesises the relationships between the constructs.
Findings
National power moderates the impact of cross-border charitable activities on host- and home-country consumers. In particular, compared to countries with high national power, countries with low national power undertaking cross-border charitable activities will receive more positive reactions from the host-country consumers, and, conversely, more negative reactions from the home-country consumers.
Research limitations/implications
From the consumer perspective, this study finds that brand cross-border charitable activities have different influences on consumers in different countries because of an identity transformation mechanism that exists between the “insiders” and the “outsiders”, which is different from the assumptions of western theories.
Practical implications
The findings provide insights for undertaking brand cross-border charitable activities.
Originality/value
Previous studies, which are based on social identity categorisation, assume that cross-border charitable activities have a more positive impact on home-country consumers than host-country consumers. However, this study adopts the research paradigm of social identity relationisation and draws an opposite conclusion, which not only expands the theory of local intergroup interaction, but also clarifies how brand cross-border charitable activities influence Chinese consumers.
Details