Behavior Of Media Research Articles

Does mindless scrolling hamper well-being? Combining ESM and log-data to examine the link between mindless scrolling, goal conflict, guilt, and daily well-being

Abstract This manuscript presents findings from a preregistered mixed-method study involving 67,762 ecological momentary assessments and behavioral smartphone observations from 1,315 adults. The study investigates (a) momentary associations between mindless scrolling, goal conflict, and guilt over smartphone use, and (b) whether guilt experiences during the day culminate into lower well-being. Results indicate that individuals experienced more guilt over their smartphone use when they had mindlessly scrolled for a longer period and that experienced goal conflict partially mediated this relationship. Daily analyses revealed that mindless scrolling was also associated with small negative changes in well-being, and this relationship was partially mediated by guilt experienced over the same day. Individuals with less self-control were more prone to experiencing goal conflict after mindlessly scrolling. These findings indicate that although mindless scrolling may seem a relatively harmless media behavior, it may have both momentary and downstream negative implications for well-being.

A Systematic Literature Review on Cyberbullying in Social Media: Taxonomy, Detection Approaches, Datasets, And Future Research Directions

In the area of Natural Language Processing, sentiment analysis, also called opinion mining, aims to extract human thoughts, beliefs, and perceptions from unstructured texts. In the light of social media's rapid growth and the influx of individual comments, reviews and feedback, it has evolved as an attractive, challenging research area. It is one of the most common problems in social media to find toxic textual content. Anonymity and concealment of identity are common on the Internet for people coming from a wide range of diversity of cultures and beliefs. Having freedom of speech, anonymity, and inadequate social media regulations make cyber toxic environment and cyberbullying significant issues, which require a system of automatic detection and prevention. As far as this is concerned, diverse research is taking place based on different approaches and languages, but a comprehensive analysis to examine them from all angles is lacking. This systematic literature review is therefore conducted with the aim of surveying the research and studies done to date on classification of cyberbullying based in textual modality by the research community. It states the definition, , taxonomy, properties, outcome of cyberbullying, roles in cyberbullying along with other forms of bullying and different offensive behavior in social media. This article also shows the latest popular benchmark datasets on cyberbullying, along with their number of classes (Binary/Multiple), reviewing the state-of-the-art methods to detect cyberbullying and abusive content on social media and discuss the factors that drive offenders to indulge in offensive activity, preventive actions to avoid online toxicity, and various cyber laws in different countries. Finally, we identify and discuss the challenges, solutions, additionally future research directions that serve as a reference to overcome cyberbullying in social media.

The Rise of Intelligent Reflecting Surfaces in Integrated Sensing and Communications Paradigms

The intelligent reflecting surface (IRS) alters the behavior of wireless media and, consequently, has potential to improve the performance and reliability of wireless systems such as communications and radar remote sensing. Recently, integrated sensing and communications (ISAC) has been widely studied as a means to efficiently utilize spectrum and thereby save cost and power. This article investigates the role of IRS in the future ISAC paradigms. While there is a rich heritage of recent research into IRS-assisted communications, the IRS-assisted radars and ISAC remain relatively unexamined. We discuss the putative advantages of IRS deployment, such as coverage extension, interference suppression, and enhanced parameter estimation, for both communications and radar. We introduce possible IRSassisted ISAC scenarios with common and dedicated surfaces. The article provides an overview of related signal processing techniques and the design challenges, such as wireless channel acquisition, waveform design, and security.

Modelling the factors that determine online news-sharing behaviour of social media users: The role of perceived message and online environmental characteristics

This study modelled the online environment characteristics and message characteristics that predict news sharing among social media users. This study’s data were obtained from a cross-sectional national survey conducted in Nigeria. Qualtrics was used to recruit data from 1320 participants in Nigeria. The participants were recruited via a stratified quota sampling which reflected the country’s census statistics for gender and age. We found the message characteristics to predict news-sharing behaviour among social media users in Nigeria. By implication, the characteristics of a message encountered online influence the news-sharing behaviour of social media users. We also found that the online environment characteristics predict news-sharing behaviour, which implies that the external factor, that is, the relationship a user has with his network members, predicts sharing behaviour. Some theoretical and practical implications were provided to conclude the study.

Students' Instagram Social Media Behavior A Study at Aisyiyah Boarding School, Indonesia

There has been studies on social media use in Asia, especially in Indonesia. However, not many of them exclusively emphasize on one particular homogeneous community based on religion aspect. This paper aims to describe the use of Instagram among muslimah students in an Islamic Boarding School in West Java, Indonesia. Specifically, this study portrays how muslimah students use and behave during their time using Instagram. This paper also tries to display their understanding on the emergence of safety and security setting function. The data were taken from online questionnaires shared to muslimah students at Aisyiyah Boarding School. The questions are open and closed questions. The research method used is a descriptive quantitative method. The results show that their social media behaviors are positively formed in an environment that supports well-scheduled activities. They only use Instagram occasionally, especially when the teachers ask them to submit tasks there. They rarely post personal contents that have no correlation with school assignments. Most of them use the “block comments and users” setting to keep their account private and safe. They claimed themselves as a non-Instagram addicts as they never experience the same fun feeling when they socialize face-to-face with their friends.
 Keywords: social media study, Muslimah students, Instagram users behavior

An Empirical Mapping of Environmental Protection and Conservation Nonprofit Discourse on Social Media

This article is a comprehensive empirical overview of environmental protection and conservation nonprofits’ discourse on social media. To what extent have these nonprofits framed climate change in their public discourse and how has it evolved over time? How do organizational characteristics and resources affect their social media behavior? To address our research questions, we use machine learning with texts—specifically topic modeling—to track the activity of 120 environmental nonprofits during a 14-year time span on X, formerly known as Twitter. Our analysis of more than 1.3 million tweets shows that climate change, although not closely aligned with the missions for more than half of the top tweeting organizations included in our sample, has consistently been a prevalent priority issue on their social media agendas for more than a decade. This heightened attention to climate change discourse by the environmental nonprofit sector denotes their uniform efforts to inspire government for climate action.

On Characterization of Shear Viscosity and Wall Slip for Concentrated Suspension Flows in Abrasive Flow Machining.

In the realm of abrasive flow machining (AFM), precise finishing and maintaining dimensional accuracy have remained challenging due to non-uniformities in the AFM process and complexities associated with the abrasive media's shear viscosity and wall slip behavior. By addressing these challenges, this study introduces a comprehensive framework, combining theoretical foundations, measurement techniques, and experimental setups. Utilizing capillary flow, a novel compensation strategy is incorporated within the Mooney method to counter entrance pressure drop effects. This enhanced capillary flow method emerges as a promising alternative to the conventional Cox-Merz empirical rule, enabling precise characterization of wall slip behavior and shear viscosity, particularly at elevated shear rates. The abrasive media exhibit a Navier nonlinear wall slip, as highlighted by the Mooney method. Rigorous verification of the proposed methodologies and models against supplemental experiments showcases a high degree of congruence between predicted and observed results, emphasizing their accuracy and broad application potential in AFM. This research illuminates the intricacies of the abrasive media's behavior, accentuating the need for meticulous characterization, and provides a robust foundation for genuine modeling and predictions in material removal within AFM.

Impact of particle elongation on the behavior of round and angular granular media: Consequences of particle rotation and force chain development

We developed a 2D discrete element model to simulate shearing response of elongated round and angular particles. Model was calibrated and validated by comparing numerical results with corresponding biaxial shearing tests on circular (round) and hexagonal (angular) rods at microscopic and macroscopic scales. Then, the systematic effect of particles aspect ratio was investigated on quasi-static shearing response of round and angular granular materials. Macroscopically, we observed a nonlinear tendency wherein as the aspect ratio decreased from 1, the critical state stress ratio initially increased, reaching a maximum, followed by a decreasing trend. This effect was more prominent in round samples. Microscopically, decreasing the aspect ratio from 1 reduced particle rotations and increased the mean coordination number. Elongated particles exhibited significant contact anisotropy, forming irregular force chains, facilitating interparticle sliding, and reducing overall strength. Additionally, we explored the impact of the interparticle friction coefficient. A high value of interparticle friction coefficient led to a monotonically increasing strength with elongation, underscoring the importance of accurately calibrating microscopic friction coefficients.

Automated hanging water column for characterizing water retention and hysteresis of coarse‐textured porous media

AbstractModeling and characterizing hysteretic water retention is critical for predicting hydrodynamic behavior in porous media. This is especially true in coarse‐textured media used in geotechnical engineering, greenhouse, and landscape industries, where subtle changes in water status may lead to plant stress. However, based on the traditional hanging water column method, water retention measurements are laborious and time consuming because of the stepwise manual water potential adjustments and wait‐time requirements for equilibrium conditions to develop. Therefore, we designed and fabricated an automated system to collect wetting‐ and drying‐water retention data from coarse porous media. The basic system consisted of (1) a compound pressure transducer (± 70‐cm range) providing both the porous medium's volumetric water content (θ) and matric potential (h) determinations, (2) a 70‐cm linear actuator to vertically position a 50‐mL burette, and (3) a diffuse laser distance sensor positioned by a 10‐cm linear actuator to monitor the burette's vertical position relative to the sample position. This automated system determined the initial drying process beginning with a fully saturated sample (h = 0 cm) and determined subsequent wetting‐ and drying‐water retention curves. Our automated water retention measurements in quartz sand (ASTM C778‐21) exhibited maximum‐ and minimum‐standard deviation in θ of 0.013 and 0.00044 cm3 cm−3, respectively. Parameters of the hysteretic water retention model of quartz sand were characterized using repeated measurements. Results of this research included the creation of an automated water retention system and the well‐characterized hydraulic parameters for the original well‐graded and narrowly sieved particle sizes of quartz sand.

Personality Factors and Their Roles on Individuals Modeling Social Media Trends and Behaviors

Personality Factors and Their Roles on Individuals Modeling Social Media Trends and Behaviors

Micromechanical model to predict the effect of temperature on the behavior of unsaturated porous media

Micromechanical model to predict the effect of temperature on the behavior of unsaturated porous media

Corrosion Behavior in Different Media of Dissimilar Super Duplex Stainless Steel 2507 and Austenitic Stainless Steel 316 Welding by Using GTAW Process with Filler Type 316L

The Super duplex stainless steel is the best of the stainless steel types because duplex stainless steel contains two phases, ferritic and austenitic, which promote this alloy's mechanical and corrosion properties compared to other types. This study will investigate the corrosion behaviour of weld metal and base metals in acidic and salty media. At 20 C, hydrochloric acid (1M, 3M, and 5M) was studied beside sodium chloride NaCl (1 wt%, 3.5 wt%, and 5 wt%). The potentiostat test results show that the effect of HCl is more aggressive than NaCl in all cases, as HCl is a strong acid. The results showed the 316 base metal being the weakest area compared with others (2507 BM and W.M.). The microstructure has been checked before and after the corrosion test and pitting corrosion has been found in the 316 base metal only, while the weld metal and 2507 base metal surfaces were free of pitting influence. Due to the welding technique and using a cooper back strip, the microstructure shows minor grain growth in the heat-affected zones (HAZ) on both weld sides. The micro-hardness test revealed that the duplex stainless steel had a higher value than the weld metal and the 316-base metal. The weld metal had a minor increase over the base metal because of the migration of the elements like chromium and nickel.

COVID-19 anxiety, COVID-19 media exposure, and knowledge and attitudes towards COVID-19: A literature review

The COVID-19 pandemic has had a significant impact on mental health, with anxiety being one of the most common symptoms. This study investigated the relationship between COVID-19-related anxiety levels, media coverage of COVID-19, and knowledge and behavior of COVID-19. The study found that COVID-19 anxiety levels were higher among people who had been quarantined, had been exposed to false information about COVID-19, or had a lower level of education. Media coverage of COVID-19 was also found to be a significant predictor of anxiety levels, with people who were more exposed to negative news stories being more likely to experience anxiety. Studies also found that COVID-19 anxiety levels were correlated with knowledge and behavior of COVID-19. People with higher anxiety levels were less likely to have accurate knowledge about COVID-19 and were more likely to engage in risky behaviors, such as not wearing a mask or social distancing. Findings of this study suggest that COVID-19 anxiety is a complex phenomenon that is influenced by a variety of factors, including media coverage, knowledge, and behavior. These findings have important implications for public health interventions aimed at reducing anxiety and promoting healthy behaviors during the COVID-19 pandemic.

The potential of automated classification to categorise police force tweeting behaviours: leading the way to large scale analysis

ABSTRACT Police activity on social media has emerged as a significant and expanding area of research. However, the existing body of research has predominantly adopted qualitative methods or focused on small-scale samples for quantitative analysis. This study presents a novel approach to analysing police social media behaviours, employing automated classification methods to generate a substantial sample of categorised police tweets. Encompassing over 40,000 tweets from five United Kingdom forces, collected over a three-year period, this dataset represents one of the largest evaluated samples in the domain of police social media research. A core objective of this research is to investigate the extent to which police tweeting behaviours align with three common categories identified in the literature: providing information, engagement, and intelligence gathering. To achieve this, a two-pronged methodology is employed, combining manual content analysis and an applied automated classification approach. This comprehensive method aims to create a sample of classified police tweets, effectively representing their diverse tweeting behaviours. The classicisation process involves the training and testing of three automated models, namely naïve Bayes, logistic regression, and XGBoost, evaluating the accuracy of their results to ensure a robust and reliable classification outcome. Furthermore, the resulting sample is subject to additional in-depth analyses. The exploration encompasses various facets of tweet content, style, overall usage, and adaptability across different police forces. Additionally, the research considers public interactions with the police tweets. These analyses are conducted for each force and class, thereby establishing connections between social media interactions and their potential impact on highlighted agendas.

Microfluidic experiments and numerical modeling of pore-scale Asphaltene deposition: Insights and predictive capabilities

Pore-scale asphaltene deposition not only affects reservoir permeability and hydrocarbon production efficiency but also impacts reservoirs performance used in other applications, such as geothermal and CO2 storage. The limited availability of comprehensive experimental data has impeded the development of precise predictive models for deposition behavior. This study employs real-time microfluidic experiments and a Lattice Boltzmann-Immersed Boundary numerical model to investigate pore-scale asphaltene deposition. Experimental results directly observe porosity reduction in diverse pore geometries, offering a detailed explanation of asphaltene deposition phenomena. The LB-IB model accurately replicates complex deposition behavior with over 93% agreement with experimental results across various geometries, using only two adjustable parameters. This enables precise predictions of asphaltene phase behavior in porous media. Sensitivity analyses explore the influence of reservoir geometry, flow rates, and asphaltene concentrations on deposition behavior, underscoring their significant impact on porosity reduction and emphasizing the importance of understanding asphaltene deposition. Additionally, the study compares the proposed model to the Wang-Civan model, showcasing its superior accuracy in capturing deposition mechanisms, and suggests modifications to include an upper limit for deposition when throats are entirely filled with asphaltene. This study improves our understanding of pore-scale asphaltene deposition, aiding in optimizing hydrocarbon extraction practices and industry efficiency.

A consistent multiscale mechanical formulation for media with randomly distributed voids

In this work we are interested in constructing a multiscale framework for solid media featuring a random distribution of voids. The reliability of standard lower bound multiscale models is questionable when voids reach the boundary, and the problem becomes critical when they are randomly arranged over the micro-cell (MC) boundary, such that periodic boundary conditions are not an option to be considered. This work presents a novel multiscale mechanical formulation to model the material behavior of media featuring such kind of heterogeneous constitution. The multiscale model is built within the framework posited by the Method of Multiscale Virtual Power. The original contribution lies at the core of the gradient homogenization formula, which generalizes existing strategies. Such generalized homogenization approach results in new Minimally Constrained Kinematical Multiscale Model (MCKMM). Moreover, alternative – kinematically more constrained with respect to the MCKMM – boundary conditions are proposed in order to obtain a wide family of multiscale sub-models (characterized by corresponding sub-spaces of the space associated with the minimally constrained model), which can be useful in practical applications. Numerical experiments are reported that provide support to the concepts introduced in this work.

Spontaneous imbibition behavior in porous media with various hydraulic fracture propagations: A pore-scale perspective

Spontaneous imbibition behavior in porous media with various hydraulic fracture propagations: A pore-scale perspective

Consumers' Perceptions of Brand Equity and The Relationship of Brand Love and Its Effect on Social Media Behaviors

Bu çalışma tüketicilerin marka değeri algılamalarının Aaker’ın (1991) belirlemiş olduğu boyutlara göre; marka farkındalığı, marka çağrışımları, algılanan kalite ve marka sadakati üzerinden her birinin marka aşkı üzerindeki etkisini belirlemek, marka aşkının marka değeri üzerindeki etkisini belirlemek ve marka değeri algılamaları ile marka aşkının tüketicilerin sosyal medyadaki davranışları üzerindeki etkisini belirlemek amacıyla yapılmıştır. Çalışma 614 katılımcının katılımıyla gerçekleşmiştir. Çalışmada hazırlanan ankette Aaker’ın (1991) marka değerleme modeli ve Carroll ve Ahuvia, (2006) Marka Aşkı ölçeği kullanılmış olup bu ölçekler 5’li likert soru tipi ile katılımcılara sorulmuştur. Çalışmada katılımcılarda daha öncesinde pilot çalışma ile hazırlanan “en sevilen marka” listesinden birisini seçmeleri istenmiş, yanıtları o markaya göre yanıtlamaları istenmiştir. Katılımcılardan çevrimiçi anket yolu ile veriler toplanmış olup, toplanan veriler SPSS paket programı yardımı ile analiz edilmiştir. Araştırma sonucuna göre, marka değeri hem genel olarak hem de her bir boyut açısından tüketicilerin marka aşkını etkilemektedir. Ayrıca marka aşkı tüketicilerin marka değerleme algılarını etkilemektedir. Bununla birlikte marka değeri algılamaları ve marka aşkı tüketicilerin sosyal medya platformlarında markaya ilişkin davranışlarını etkilemektedir.

Modelling Porous Cementitious Media with/without Integrated Latent Heat Storage: Application Scenario

This paper presents a methodological approach for the evaluation of the thermal behavior of cementitious porous media with/without integrated latent-heat thermal energy storage (LHTES). To achieve this goal, the Lewis-Nielsen model has been calibrated to predict the insulation properties of mineralized foamed concretes. Two pore-related microstructural fitting parameters, A and Φm, are presented according to the available data in the literature. In this regard, new findings are implemented for the classification of pore structure and prediction of the homogenized thermal conductivity of two-phase cementitious foams with or without phase change materials. The calibration and predictive analyses have been extended to a wide range of experimental data, including variation of binder types, porosities, and latent components. The presented analytical approach appears to agree well with experimental results and can be employed in the design of two-phase mineral foam materials. Then, to assess the thermal behavior of the predicted insulating envelopes, a one-dimensional (1D) enthalpy-based model is used which combines Fourier’s law of heat conduction, the first law of thermodynamics, Lewis-Nielsen conductivities, and the mixture theory for LHTES additions. The results demonstrated the importance of volumetric heat capacity for the thermal inertia of building envelopes.

Lonely, impulsive, and seeking attention: Predictors of narcissistic adolescents’ antisocial and prosocial behaviors on social media

Narcissistic youth use social media to engage in a variety of self-promotional behaviors, which have either antisocial or prosocial characteristics. Differing views exist to explain the processes underlying narcissistic self-promotion, either characterizing these actions as intentional, or as impulsive. This study compared intentional attention-seeking and impulsivity as potential mediators of relations between narcissism and both aggressive (i.e., cyberbullying) and prosocial online behavior, and examined whether youth’s loneliness might strengthen these associations. Among Chinese early adolescents (N = 213, Mage = 13.26), narcissism positively predicted youth-reported cyberbullying offending and online prosocial behavior. Loneliness moderated the link between narcissism and attention-seeking, but not impulsivity. Among adolescents higher in loneliness, narcissism indirectly predicted cyberbullying and online prosocial behaviors via attention-seeking. These results highlight narcissism, loneliness, and their interplay as potential predictors of youth’s social media behaviors. Links with attention-seeking, in particular, suggest that educators and practitioners might target youth’s conscious expectations for social rewards when counseling narcissistic adolescents about self-promotional social media use.