Social media platforms like Instagram have increasingly become venues for online abuse and offensive comments. This study aimed to enhance user security to create a safe online environment by eliminating hate speech and abusive language. The proposed system employed a multifaceted approach to comment filtering, incorporating the multi-level filter theory. This involved developing a comprehensive list of words representing various types of offensive language, from slang to explicit abuse. Machine learning models were trained to identify abusive messages through sentiment analysis and contextual understanding. The system categorized comments as positive, negative, or abusive using sentiment analysis algorithms. Employing AI technology, it created a dynamic filtering mechanism that adapted to evolving online language and abusive behavior. Integrated with Instagram while adhering to ethical data collection principles, the platform sought to promote a clean and positive user experience, encouraging users to focus on non-abusive communication. Our machine-learned models, trained on a cleaned Arabic language dataset, demonstrated promising accuracy (75.8%) in classifying Arabic comments, potentially reducing abusive content significantly. This advancement aimed to provide users with a clean and positive online experience.
This paper aims to analyze the present conditions of the social responsibility ecosystem in online audiovisual enterprises in the digital age. It focuses on the governance of social responsibility in these enterprises and conducts an in-depth analysis of the problems and influencing factors related to the social responsibility aberrations of online audiovisual enterprises. Drawing upon social responsibility theory and collaborative governance theory, this research constructs a social responsibility guidance and governance system guided by the public, supported by the voluntary fulfillment of responsibilities by online audiovisual enterprises, and based on the collaborative participation of diverse stakeholders. It explores and optimizes the implementation pathways of this system, providing theoretical support and practical guidance for promoting the sustainable development of online audiovisual enterprises. Furthermore, it aims to contribute to the creation of a harmonious Internet ecosystem.
Both farmers and traders benefit from trade networking, which is crucial for the local economy. Therefore, it is crucial to understand how these networks operate, and how they can be managed more effectively. Throughout this study, we examine the economic networks formed between farmers and traders through the trade of food products. These networks are analyzed from the perspective of their structure and the factors that influence their development. Using data from 18 farmers and 15 traders, we applied exponential random graph models. The results of our study showed that connectivity, Popularity Spread, activity spread, good transportation systems, and high yields all affected the development of networks. Therefore, farmers’ productivity and high market demand can contribute to local food-crop trade. The network was not affected by reciprocity, open markets, proximity to locations, or trade experience of actors. Policy makers should consider these five factors when formulating policies for local food-crop trade. Additionally, local actors should be encouraged to use these factors to improve their network development. However, it is important to note that these factors alone cannot guarantee success. Policy makers and actors must also consider other factors such as legal frameworks, economic policies, and resource availability. Our approach can be used in future research to determine how traders and farmers can enhance productivity and profit in West Africa. This study addresses a research gap by examining factors influencing local food trade in a developing country.
With the penetration of the Internet, virtual groups have become more and more popular. The reliability and accuracy of interpersonal perception in the virtual environment is an intriguing issue. Using the Social relations model (SRM) [1], this paper investigates interpersonal perception in virtual groups from a multilevel perspective. In particular, it examines the following three areas: homophily, identification, and individual attraction, and explores how much of these directional and dyadic relational evaluations can be attributed to the effect of the actor, the partner, and the relationship.
The increasing prevalence of technology in society has an impact on young people's language use and development.Greeklish is the writing of Greek texts using the Latin instead of the Greek alphabet, a practice known as Latinization, also employed for many non-latin alphabet languages.The primary aim of this research is to evaluate the effect of Greeklish on reading time.A sample of 732 young Greeks were asked about their habits when communicating through e-mail and social media with their friends and they then participated in an experiment in which they were asked to read and understand two short texts, one written in Greek and the other in Greeklish.The findings of the research show that nearly one third of the participants use Greeklish.The results of the experiment conducted reveal that understanding is not affected by the alphabet used but reading Greeklish is significantly more time consuming than reading Greek independently of the sex and the familiarity of the participants with Greeklish.The findings suggest that amending social and communication media with software utilities related to Latinization such as language identifiers and converters may reduce reading time and thus facilitate written communication among the users.
Purpose/Significance: This study aims to define the concept of leading cadres new media usage in China specifically, and to describe and analyze the forms and typical cases and characteristics of leading cadres new media in different stages.Method/Process: Based on the themes and contents of a few media accounts of leading cadres at different ranks, we summarizes leading cadres new media usage in a systematic perspective and content analysize method.Result/Conclusion: The study defines the concept of Leading Cadres' new media from the perspective of media practice, determine its position as a media communication platform in the government affairs new media communication system and its relationship with the other elements, and then systematically review the evolution of its media practice from personal website, blog, microblog and microblog to WeChat, live show.On this basis, with the Harold Lasswell communication model, this article summarizes leading cadres new media communication characteristics from five aspects: content producer, content, channel, audience, and effect.Future studies may also enhance the empirical research from the effect perspective.
Systematic Review and Meta-analysis are techniques which attempt to associate the findings from similar studies and deliver quantitative summaries of the research literature [1].The Systematic review of research literature identifies the common research methods, research design, sample size, parameters used, survey instruments, etc. used by the group of researchers.This study intends to fulfill this purpose in order to identify common research mythologies, dependent variables, sample sizes, moderators and mediators used in the field of analysing technology adoption based studies that utilizes the UTAUT2 model.This research collected over 59 published articles and conducted descriptive analytics.The results have revealed performance expectancy/perceived usefulness, trust and habit as the best predictors of consumer behavioural intentions towards the adoption of mobile application.Behavioural intention was the best predictor of use behaviour among the 57 articles selected.274 was the mean sample size of research with 25 mean questionnaire items.SPSS and AMOS were the most common softwares used in all 57 studies, and 32 of those studies used UTAUT1 model while 14 researches incorporated the UTAUT2 model.There were also two promising predictors such as perceived risk on behavioural intention and habit on use behaviour.
In project-based organizations knowledge is a critical resource used to develop and deliver products and services with a high level of quality.Therefore, a systematic and sustainable process is necessary to coordinate knowledge management, project management and product lifecycle.This scenario predominates in companies focused on the creation and maintenance of information systems.This article presents an exploratory study based on a framework that integrates cognitive, managerial, and operational processes in a public Brazilian organization that provides services in the area of information and communications technology, focusing on the construction and maintenance of information systems.Those processes are operationalized by three management models considering knowledge, project, and software development processes.Our proposal aims to understand the relationships between those three management models and their influence on the software development process in the organization under study.Our premise is based on the principle that cognitive management, project management, and software development management must be integrated to fulfill the demands of product development and service provision.The research data was composed of registers of working hours spent on software development and maintenance projects involving 244 people allocated to 5064 projects in the period from 2007 to 2013.The study resulted in the identification of the relationships among the three management models adopted by the organization, with emphasis on knowledge management activities, which were not directly identified, making it difficult to account for and measure them.We established a set of activities connected to each one of the knowledge management model How to cite this paper:
The objective of the research dialogues with recent studies on the presence of a favorable environment for innovation while respecting and guided by theoretical perspectives that were built by classic authors in this field of research, such as Geert Hofstede and Edgar Schein. 258 questionnaires were answered and the data obtained were analyzed using structural equation modeling (SEM) after tabulation in statistical analysis software. The research model is quantitative-descriptive and is based on the methodology developed by MIRP and later adapted by other authors. As a result of this research, it was identified that employees perceive the culture of the analyzed organization with a high level of collectivism and high cultural congruence. It was found that employees have a perception that there is a small power distance. At the end of the research, it is possible to affirm that there is a relationship between the organizational culture and the favorable environment for the development of innovations in the analyzed company.
This study investigates the measurement of social identification, interpersonal attraction, and cohesiveness in virtual groups. Different theoretical claims about relationships in computer-mediated groups rely on measurement strategies that are shown to reflect dramatically inconsistent semantic and administration features. A review of conceptual approaches and definitions for these constructs is presented. Data were collected from groups working asynchronously via the Internet under different geographic distributions, whose members completed a variety of measures related to these constructs. Analyses generated three likely dimensions of attraction. The research highlights the need for greater specificity in reports of the actual measures used in group research, and additional conceptual concerns regarding the contested relationships among these constructs.
Background: Weibo is a Twitter-like micro-blog platform in China where people post their real-life events as well as express their feelings in short texts. Since the outbreak of the Covid-19 pandemic, thousands of people have expressed their concerns and worries about the outbreak via Weibo, showing the existence of public panic. Methods: This paper comes up with a sentiment analysis approach to discover public panic. First, we used Octoparse to obtain Weibo posts about the hot topic Covid-19 Pandemic. Second, we break down those sentences into independent words and clean the data by removing stop words. Then, we use the sentiment score function that deals with negative words, adverbs, and sentiment words to get the sentiment score of each Weibo post. Results: We observe the distribution of sentiment scores and get the benchmark to evaluate public panic. Also, we apply the same process to test the mass sentiment under other topics to test the efficiency of the sentiment function, which shows that our function works well.
An understanding of the knowledge creation and diffusion process in the organizational context is extremely relevant. Because from this understanding, organizations can restructure processes, reorient teams and implement methodologies to assist in the construction of an evolutionary process of knowledge creation and diffusion aimed at sustainable growth and innovation. The theory of complex social networks has been applied in several fields to help understand organizational cognitive processes. However, these approaches still insipiently consider the analysis of the nestedness and modularity of the studied networks. In this article, we presented an approach that sought to identify patterns of nestedness and modularity in networks of affiliation of people in projects in the organizational context. The study sought to identify these patterns in affiliation networks in a public organization providing information technology services in the period from 2006 to 2013. The detection of these patterns was performed using the NODF (Nestedness metric based on Overlap and Decreasing Fill) algorithm described by [1]. The nestedness and modularity metrics can influence patterns of knowledge creation and diffusion in formal and informal networks constituted for the execution of projects in organizations. This study showed that the network structures of the organization during the study period presented a high degree of nestedness, and it was possible to identify combined structures of nestedness and modularity.
This work presents an approach to study the diffusion of knowledge in software development project teams based on the formation of complex social network structures in a public organization that offers information and communication technology services.We collected historical data on the allocation and records of hours worked by people in projects to build an affiliation network.We applied the method of reflections to analyze the data obtained.The constructed model enabled the description of the participation of project team members from the perspective of the creation and diffusion of knowledge in affiliation networks that describe the participation of people in projects, mediated by the knowledge and the capabilities developed for the execution of these projects.A contribution of this work is the construction of indicators related to the process of creation and diffusion of knowledge in the context of the execution of software development and maintenance projects, based on the concepts of diversification and ubiquity applied to the process of knowledge diffusion; an additional contribution is the presentation of an application of the method of reflections in an organizational context applied to the creation and diffusion of knowledge.We found that the application of management models associated with the collaborative method applied to the project development process contributed to the joint growth of diversified and more specialized knowledge alongside the knowledge considered more generic and ubiquitous.Our results show that contrary to previous expectations based on assumptions established at the beginning of the study, we concluded that in six of the seven subnetworks obtained in the period between
