Search results

Considering the popularity and addictive attributes of microblogging, the purpose of this paper is to explore the key drivers of the microblogging addiction tendency, and to investigate the causal relationship between microblogging usage and addiction tendency through the lens of the uses and gratifications (U&G) theory.

By extending the U&G theory to accommodate the negative consequences of gratification, a research model that explains the relationships among microblogging use, gratification and addiction tendency was developed and empirically examined based on the data collected from 520 microblogging users in China.

The results showed that different types of microblogging use lead to different categories of gratification to different extents, while different categories of gratification play different roles in determining the level of addiction tendency. Specifically, the effect of content gratification on addiction is marginal, while social gratification has significant effects on all dimensions of addiction tendency.

The present study has both theoretical and practical implications. From a theoretical perspective, unlike many previous studies applied the U&G theory to explore the positive outcomes of media uses, this paper extends the U&G by including addiction tendency as a negative psychological outcome of U&G., resulting a research framework (use-gratification-addiction framework). Meanwhile, this paper contributes to the extending literature by examining the constructs of U&G at a granular level and investigated the causal relationship between “uses” and “gratifications.”

Shear stresses have a considerable influence on the characteristics of lubricants and become significant at high rotating speeds. This study aims to investigate the influences of shear cavitation (SC) on loading capacity of journal bearings.

A principal normal stress cavitation criterion based on the stress applied to flowing lubricant in journal bearings is developed and used to investigate SC in journal bearings. A computational fluid dynamic (CFD) model for calculating the loading capacity is established using this criterion. After validation with experimental results, the loading capacity is calculated under different conditions.

The calculation results indicate that SC intensifies when viscosity, speed and eccentricity increase. Angle of loading capacity with SC is larger than that without SC. The magnitude of loading capacity with SC is smaller than that without SC due to the decrease in the ultimate pressure. In addition, the magnitude difference between the loading capacity with and without SC increases when viscosity, speed and eccentricity increases.

Present research can provide some guidance for calculating the loading capacity when a journal bearing is operating at high speed or with a high viscosity lubricant.

Surface texturing has been proven as an effective means of contact performance enhancement. However, limited work has been done to investigate the regular relationship to solve the multi-parameters problem of textures, and inertia effect and elastic deformation were seldom considered together in previous optimization work. This paper aims to quantitatively obtain the relationship between the textured depth and liquid film thickness and find the effect of deformation on the optimal textured height ratio in elastic parallel sliders.

Numerical models of hydrodynamic lubrication are established based on the computational fluid dynamic method. Elastic deformation is considered through fluid–structure interaction (FSI) method. Using response surface optimization method, textured parallel sliders are optimized with maximum loading capacity as the objective.

The results show that the optimal height ratios are all within the range of 0.60-0.65 when textured parallel sliders are considered as rigid. After considering the effect of elastic deformation, loading capacity drops and is reduced more obviously with a decrease in the elastic moduli. The optimal height ratios are within the range of 0.60-0.63, which shows that FSI has a considerable influence on loading capacity but has no significant influence on the optimal height ratio.

The present research provides a theoretical reference for engineering application of elastic textured parallel sliders.

We examine how social exclusion and temporal distance (i.e. being socially excluded in the present or the anticipation of exclusion in the future) shape whether people choose hedonic or utilitarian products.

We conduct four experiments to test the hypotheses. Study 1a and study 1b provide the initial evidence that consumers strategically engage in differentiation in response to social exclusion in the present and in the future. Study 2 and study 3 replicate the basic interaction effect of social exclusion and temporal distance on product choices and test the underlying mechanism.

We find that temporal distance affects consumer product choices through people’s coping strategies. When consumers are socially excluded, they are more likely to have a problem-solving tendency and more likely to choose utilitarian products. In contrast, when consumers imagine being socially excluded in the future, they are more likely to have to use emotions to solve problems and choose hedonic products.

Our study contributes to the literature in several ways. First, it deepens our understanding of the psychological drivers of social exclusion in consumer research. Second, it offers insights into understanding prior findings that document both problem-solving and emotion-regulating behavior in response to social exclusion. Third, by showing that social exclusion and temporal distance can influence the type of products selected, our findings contribute to a new stream of work that examines the impact of people’s fundamental desire for control on consumer behavior.

Timely detection of emergency events and effective tracking of corresponding public opinions are critical in emergency management. As media are immediate sources of information on emergencies, the purpose of this paper is to propose cross-media analytics to detect and track emergency events and provide decision support for government and emergency management departments.

In this paper, a novel emergency event detection and opinion mining method is proposed for emergency management using cross-media analytics. In the proposed approach, an event detection module is constructed to discover emergency events based on cross-media analytics, and after the detected event is confirmed as an emergency event, an opinion mining module is used to analyze public sentiments and then generate public sentiment time series for early warning via a semantic expansion technique.

Empirical results indicate that a specific emergency can be detected and that public opinion can be tracked effectively and efficiently using cross-media analytics. In addition, the proposed system can be used for decision support and real-time response for government and emergency management departments.

This paper takes full advantage of cross-media information and proposes novel emergency event detection and opinion mining methods for emergency management using cross-media analytics. The empirical analysis results illustrate the efficiency of the proposed method.

The proposed method can be applied for detection of emergency events and tracking of public opinions for emergency decision support and governmental real-time response.

This research work contributes to the design of a decision support system for emergency event detection and opinion mining. In the proposed approaches, emergency events are detected by leveraging cross-media analytics, and public sentiments are measured using an auto-expansion of the domain dictionary in the field of emergency management to eliminate the misclassification of the general dictionary and to make the quantization more accurate.

Surface textures have been widely used in thrust bearings as a means of enhancing the tribological performance. The effect of textures with a spiral distribution on the lubrication characteristics of thrust bearings has not been fully covered. This paper aims to investigate and find the optimal structure and distribution parameters of textures with the maximum loading capacity and minimum friction force as goals.

Combining the multi-objective optimization method based on the non-dominated sorted genetic algorithm-II with response surface methodology, the key textured parameters are optimized. Local sensitivity analysis is used to evaluate the impact level of each parameter.

Spiral distribution of textures can effectively improve the lubrication performance of the thrust bearing compared with the linear distribution. The distribution with high amplitudes and high cycle numbers will weaken the spiral effect and destroy the high-pressure region. Through the multi-objective optimization of the textured structure and distribution parameters, the loading capacity demonstrates a 55.05per cent improvement compared to the basic model. Textured width is the most sensitive parameter for both loading capacity and friction force.

Present research provides a fundamental design guide for textured thrust bearings.

The stringent requirements for environmental protection have induced the extensive applications of water-lubricated journal bearings in marine propulsion. The nonlinear dynamic analysis of multiple grooved water-lubricated bearings (MGWJBs) has not been fully covered so far in the literature. This study aims to conduct the nonlinear dynamic analysis of the instability for MGWJBs.

An attenuation rate interpolation method is proposed for the determination of the critical instability speed. Based on a structured mesh movement algorithm, the transient hydrodynamic force model of MGWJBs is set up. Furthermore, the parameters’ analysis of nonlinear instability for MGWJBs is conducted. The minimum water film thickness, side leakage, friction torque and power loss of friction are fully analyzed.

With the increase of speed, the journal orbits come across the steady state equilibrium motion, sub-harmonic motion and limit circle motion successively. At the limit circle motion stage, the orbits are much larger than that of steady state equilibrium and sub-harmonic motion. The critical instability speed increases when the spiral angle decreases or the groove angle increases. The minimum water film thickness peak is at the rotor speed of 4,000 r/min for the MGWJB with Sa = 0°. As rotor speed increases, the side leakage decreases slightly while the friction torque and the power loss of friction increase gradually.

Present research provides a beneficial reference for the dynamic mechanism analysis and design of MGWJBs.

The growing demand of efficiency and economy has led to a dramatic increase of the operating speed of the journal bearing, with a higher temperature distribution. This paper aims to investigate the three-dimensional temperature distribution of journal bearings.

A thermo-hydrodynamic lubrication model of a journal bearing was established based on the full 3D CFD method. A two-sided wall was used to include the conjugate heat transfer effect. The temperature-dependent characteristics of lubrication and cavitation impact were also included. The simulation results well agreed with the experimental results. Based on this method, the three-dimensional temperature distribution was analyzed under different operating conditions.

The temperature distribution in the radial direction had a difference. An increase of speed and de-crease of inlet temperature promoted temperature differences in the higher temperature zone and the increasing temperature zone, respectively. However, the inlet pressure had less influence on these differences. The temperature distribution was basically the same at a lower bearing conductivity. As the conductivity increased, the radial temperature difference was increased.

The temperature distribution in the radial direction was found under different operating conditions, and the present research provides references to understand the three-dimensional temperature distribution of journal bearings.

Despite the extensive academic interest in social media sentiment for financial fields, multimodal data in the stock market has been neglected. The purpose of this paper is to explore the influence of multimodal social media data on stock performance, and investigate the underlying mechanism of two forms of social media data, i.e. text and pictures.

This research employs panel vector autoregressive models to quantify the effect of the sentiment derived from two modalities in social media, i.e. text information and picture information. Through the models, the authors examine the short-term and long-term associations between social media sentiment and stock performance, measured by three metrics. Specifically, the authors design an enhanced sentiment analysis method, integrating random walk and word embeddings through Global Vectors for Word Representation (GloVe), to construct a domain-specific lexicon and apply it to textual sentiment analysis. Secondly, the authors exploit a deep learning framework based on convolutional neural networks to analyze the sentiment in picture data.

The empirical results derived from vector autoregressive models reveal that both measures of the sentiment extracted from textual information and pictorial information in social media are significant leading indicators of stock performance. Moreover, pictorial information and textual information have similar relationships with stock performance.

To the best of the authors’ knowledge, this is the first study that incorporates multimodal social media data for sentiment analysis, which is valuable in understanding pictures of social media data. The study offers significant implications for researchers and practitioners. This research informs researchers on the attention of multimodal social media data. The study’s findings provide some managerial recommendations, e.g. watching not only words but also pictures in social media.