Towards offensive language detection and reduction in four Software Engineering communities

The growing use of social media has increased online harassment, cyberhate, and the use of offensive language. This poses significant challenges for effectively detecting and addressing such issues. Natural Language Processing (NLP) has seen considerable advancements; however, automatically identifying offensive language remains a complex task due to the ambiguous and informal nature of user-generated content and the social context in which it occurs. In this thesis, our goal is to develop methods for automatic detection of offensive language in social media. Multiple classification algorithms, including Multinomial Naive Bayes, Gaussian Naive Bayes, SVM, Logistic Regression, and LSTM, are implemented and evaluated. Key measures including accuracy, F1 score, and AUC score are used to evaluate how well these algorithms work. Results show that the Random Forest Classifier obtains an AUC score of 0.65 and an accuracy of 0.82 without word2vec. On the other hand, LSTM demonstrates a competitive AUC score of 0.78 when compared to the Random Forest Classifier. These findings provide insights into the effectiveness of different algorithms for offensive language detection. The research contributes to the field by providing valuable tools and insights to enhance Turkish language processing and prioritize online safety, particularly in combating cyberbullying and fostering a tolerant online environment. The findings also pave the way for future research endeavors in natural language processing and have practical implications for protecting individuals and promoting a secure online space.

A very important discovery has been made through the reviewed literature and theories showing existence of an intricate relationship between natural surroundings and the prevalence of offensive language, aiming to unravel the underlying dynamics that contribute to linguistic behavior in diverse environmental contexts. Through a multidisciplinary approach that integrates insights from psychology, sociology, and environmental science, the study established the impact of natural environments on the frequency, intensity, and contextual nuances of offensive language. Therefore, the purpose of this research paper was to explore the correlation between the natural surroundings and the prevalence of offensive language in society: a case study on three (3) selected communities in Lusaka district. The sample consisted of sixty (90) respondents. A representative sample of 60 adolescents and 30 parents: i.e., 20 adolescents from each named compound and 30 parents, that is, 10 from each compound were randomly selected from the three compounds in the district. Qualitative method was applied during data analysis. The results of the study indicated that environmental factors, including the natural surroundings do influence human behavior and emotions thereby adversely affecting language use in various contextual settings. It was equally revealed that exposure to nature or green spaces has a positive effect on the mental well-being, reducing stress and promoting positive mood amongst people living in low density residential compounds where the use of offensive language is less, as opposed to high density residential compounds where the use of offensive (profane) language is heavily influenced by numerous social, cultural, and personal factors among others.

Emotion analysis in text has drawn recent interests in the software engineering (SE) community. Existing domain-independent techniques for automated emotion/sentiment analysis perform poorly when operated on SE text. Thus, a few SE domain-specific tools are recently developed for detecting sentimental polarities (e.g., positivity, negativity). But, for capturing individual emotional states such as excitation, stress, depression, and relaxation, there is only one recent tool named DEVA, which uses a lexicon-based approach.

Linguists argue women's linguistic politeness is influenced by societal perceptions, but as gender equality advances, the concept of women's language evolves, involving debates on offensive language. Therefore, this study investigated the utilization of offensive language by women TikTokers in the Free Palestine campaign. The research focuses on the study of issue statements regarding the various forms of offensive language used by women TikTokers participating in the Free Palestine campaign. This study employs Battistella's (2005) theory, which posits four distinct categories of offensive language. This study employed a qualitative approach, utilizing data obtained from the transcriptions of three female TikTok users, namely Kayla, Katie, and Heba. According to the research findings, women who use TikTok employ all of Battistella's offensive language categories a total of 223 times in their videos. Among women TikTokers, the term "obscenity" is the most frequently utilized, appearing a total of 159 times. It is followed by "epithets," which appear 30 times; "profanity," which appears 19 times; and "vulgarity," which appears 15 times. This study presents empirical evidence demonstrating that the linguistic patterns exhibited by Kayla, Katie, and Heba, who are female TikTokers, deviate from the conventional characteristics of women's language, specifically in relation to the usage of swearing as described by Lakoff. Kayla, Katie, and Heba exercise a greater degree of autonomy in expressing themselves through the use of offensive language, without fear of criticism or judgment.

At Amazon, Release Engineering falls under what we call Operational Excellence: designing, implementing, maintaining, and releasing a scalable product. There is an even more basic component that is often ignored: source control. Good source control practices are necessary but not sufficient for delivering good software. Over the 25+ years source control has been used, each tool has come with its own set of pitfalls: CVS, subversion, mercurial, and most recently, git. For decades, the unwritten rule has been for each organization to identify and mitigate these pitfalls independently, with an expectation that the next innovation would remediate it. This approach scales neither for large organizations such as Amazon nor the software engineering community at large. The real source of this dysfunction—remote collaboration between software engineers—must be examined and ultimately fixed. In the interim, it is up to the engineering community to share practices independent of software process to make up the difference. At its core, source control is a fundamental tool of software engineers, expected to be easily understood and “just work;” this assumption is invalid on a number of dimensions. Neither Software Configuration Management (SCM) nor the tools used are intuitive to new practitioners, and must be taught. The changing landscape of newer tools misleads even expert users of past tools who are not screened for this critical skill. And finally, success is dependent upon synthesis of past experience and tuning a pre-determined process to both project goals and the team. Success, then, is stacked against the engineering team—so what happens when source control usage goes horribly wrong? The baseline and team end up in “Git Hell,” slowed down, or even blocked, by the very tool that facilitates collaboration and parallel development. “Git Hell” originates from various sources: poor tool design, misuse or misconfiguration of the command line interface, and lack of understanding of the “nuts and bolts” of the tool. For example, poor interface design or configuration, even with the command line interface, has widespread impact. A substantial flaw in the mechanics of git push caused substantial pain at multiple engineering firms. The interface was straightforward: a push sends all branches with updates to the server; adding the -f option forces an update; combining them proved disastrous, as an engineer with minimal knowledge of git could harm the integrity of the baseline without even realizing it. This prior version required each developer to add local configuration to his workstation, ensuring others in the future would repeat the mistake. These classes of issues are repeated at company after company, group after group—illustrating a systemic problem with git, its configuration, the instruction in its usage, and the interaction between collaborating engineers. To combat this, I generalized preventative measures as a workaround in a workshop entitled “Get out of Git Hell” that can be shared among engineers regardless of experience or process, at least until the root causes can be studied and remediated.

Artificial intelligence and recent advances in deep learning architectures, including transformer networks and large language models, change the way people think and act to solve problems. Software engineering, as an increasingly complex process to design, develop, test, deploy, and maintain large-scale software systems for solving real-world challenges, is profoundly affected by many revolutionary artificial intelligence tools in general and machine learning in particular. In this roadmap for artificial intelligence in software engineering, we highlight the recent deep impact of artificial intelligence on software engineering by discussing successful stories of applications of artificial intelligence to classic and new software development challenges. We identify the new challenges that the software engineering community has to address in the coming years to successfully apply artificial intelligence in software engineering, and we share our research roadmap toward the effective use of artificial intelligence in the software engineering profession, while still protecting fundamental human values. We spotlight three main areas that challenge the research in software engineering: the use of generative artificial intelligence and large language models for engineering large software systems, the need of large and unbiased datasets and benchmarks for training and evaluating deep learning and large language models for software engineering, and the need of a new code of digital ethics to apply artificial intelligence in software engineering.

We welcome you to the Twenty-Eighth International Conference on Software Engineering and Shanghai, China. This is the first instance of the ICSE conference series to be held in China, and it is an exciting time and place for ICSE 2006. The conference brings researchers, educators, practitioners and students together to present, exchange ideas and engage in discussions about the recent and exciting innovations and research in software engineering. Exciting sessions on practical experience, educational issues, and doctoral and new faculty symposia have been organized. The conference also includes a wide variety of tutorial, workshops and demonstration offerings. Finally, since research and markets in our host country China are continuously growing, ICSE includes a separate Far East Track for discussions on the contributions and challenges of our Chinese colleagues. We trust that this mix will provide interesting and stimulating offerings to all members of our growing community. The technical program committee is pleased to present this conference proceeding that contains the research papers of the technical program for ICSE 2006. The technical program for this conference focuses on new and innovative software engineering contributions in theory, formal methods, system building and empirical studies. The papers represent an alluring array of topics, including software design, architecture, reuse, testing, analysis, processes and formal methods. Because of the growing number of paper submission and the resulting large program committees in the past, we instituted a new two-phase reviewing process this year. Our program committee had 36 members. In the first phase, each submitted paper was reviewed by 3 reviewers: 2 from the program committee and an external reviewer from the software engineering community. We had 265 external reviewers who contributed 370 reviews for this phase. Those papers receiving the best reviews were considered in the second phase. A total of 99 papers entered the second phase. Each of these papers was reviewed by another program committee member. Thus, each accepted paper had a total of 4 reviews (3 reviews from pc members and 1 review from an external reviewer). Each rejected paper had at least 3 reviews. The pc members reviewed 24-25 papers in the two phases, a reasonable number. We feel that this system worked very well. The program committee met for two days in December, 2005 in Frankfurt, Germany. By the end of the meeting, a consensus emerged for the 36 papers in this proceedings (9% of the total submissions). There were many high quality submissions that could not be accommodated in the program; hopefully a revised version will be published elsewhere. In addition to the papers, we organized four invited sessions. One invited session focuses on empirical studies, an increasingly important component of software engineering research and practice. We also have an invited panel that addresses the value and practice of formal methods. Since software engineering techniques are growing in importance in challenging safety critical domains, we included two invited sessions: one on software engineering for automotive engineering and the other on software engineering for assisted living. We are very pleased that a notably diverse and outstanding group of three leaders of the software engineering community have agreed to present keynote speeches. The opening day keynote will be presented by Prof. Yang Fuqing, from Peking University, a woman who has been at the very forefront of the software engineering communities of research and practice in China for decades. Her perspectives on the past and future of software engineering in China will be complemented by a keynote on similar themes presented on the second day. This second keynote will be delivered by Prof. Barry Boehm, from the University of Southern California, USA. His talk will review the history of software engineering research and practice in the West over the past decades, and project it forward into the 21st century. Finally, the keynote speaker on the third day, Mr. Reinhold Achatz, from Siemens Corp., will present a complementary view of software engineering research and practice, as viewed from the perspective of one of the great multinational corporations, based in Europe. We are truly excited at the prospect that these three keynotes will provide a searching multidimensional view of our community at this time of historic convergence of communities. The continued success and high quality of the ICSE conference series would not be possible without the help and support of the software engineering community. First, we would like to gratefully acknowledge and thank all of the authors who submitted papers. We especially thank the program committee members for their efforts and commitments in reviewing the papers and securing reviews from external reviewers. They put in an extraordinary amount of their time to provide thoughtful and knowledgeable reviews. The exceptionally strong technical program represented by the papers in this proceeding could not be possible without their efforts.

This paper introduces a streamlined taxonomy for categorizing offensive language in Hebrew, addressing a gap in the literature that has, until now, largely focused on Indo-European languages. Our taxonomy divides offensive language into seven levels (six explicit and one implicit level). We based our work on the simplified offensive language (SOL) taxonomy introduced in (Lewandowska-Tomaszczyk et al. 2021a) hoping that our adjustment of SOL to the Hebrew language will be capable of reflecting the unique linguistic and cultural nuances of Hebrew. The study involves both linguistic and cultural analysis beyond Natural Language Processing (NLP). We employed manual linguistic analysis to understand the nuances of offensive language in Hebrew.An accompanying dataset, gathered on Twitter and manually curated by human annotators, is described in detail. This dataset was constructed to both validate the taxonomy and serve as a foundation for future research on offensive language detection and analysis in Hebrew. Preliminary analysis of the dataset reveals intriguing patterns and distributions, underscoring the complexity and specificity of offensive expressions in the Hebrew language.The aim of our work is to capture the complexity and specificity of offensive expressions in Hebrew beyond what automated NLP methods alone can provide. Our findings highlight the significance of considering linguistic and cultural variations when researching and correcting abusive language online. We believe that our streamlined taxonomy and associated dataset will be crucial in improving research in Hebrew language sociocultural studies, natural language processing, and offensive language detection. Our study also makes a substantial contribution to the study of low-resource languages and can be used as a model for future research on other languages.

In this paper,I first review the seminal work by Thomas Kuhn — The Structure of Scientific Revolutions — and elaborate my view on paradigm shifts in software engineering research and practice as it turns 50 years old in 2018. I then examine major undertakings of the computing profession since early days of modern computing, especially those done by the software engineering community as a whole. I also enumerate anomalies and crises that occurred at various stages, and the attempts to provide solutions by the software engineering professionals in the past five decades. After providing such a background, I direct readers attention toward emerging anomalies in software engineering, at a severity level that is causing another software engineering crisis, and suggest a set of criteria for feasible solutions. The main theme of this paper is to advocate that situation analytics, equipped with necessary definitions of essential concepts including situation and intention as parts of a new computational framework, can serve as the foundation for a new software engineering paradigm named the Situation-Centric Paradigm. In this framework, situation is considered a new abstraction for computing and is clearly differentiated from the widely accepted existing abstractions, namely function and object. I argue that the software engineering professionals will inevitably move into this new paradigm, willingly or unwillingly, to empower Human-Embedded Computing (HEC) and End-User Embedded Computing (EUEC), much more than what they have done with traditional human-centered or user-centric computing altogether. In the end, I speculate that an ultimate agile method may be on the rise, and challenge readers to contemplate “what if" hundreds of thousands “end-user developers" emerge into the scene where the boundaries between end users and developers become much more blurred.

Introduction and Vision I am honored to be taking over as Editor in Chief of the IEEE Transactions of Software Engineering (TSE). Jeff Kramer will be a hard act to follow, but I am immensely grateful to him for handing over the journal in such a healthy state, and for helping me learn the new job to ensure a smooth transition. It goes without saying that my primary goal as Editor is to maintain the journal’s reputation and standing as the leading forum for publishing the highest quality of research in software engineering. However, these are exciting and changing times in the world of publishing and in the discipline of software engineering, and I believe that TSE must lead the way by finding innovative ways to disseminate software engineering research and by contributing to setting and reflecting the research agenda in the field. To this end I have three medium term goals for my tenure as Editor: 1. To reemphasize the broad scope of the journal, encouraging the publication of multidisciplinary research as well as specialization in software engineering. 2. To engage with the software engineering community at large, including other journals, about the software engineering discipline, using not only the journal itself as a forum but through other professional outlets such as conferences and the web. 3. To support a debate on the nature of scholarly discourse in software engineering, such as the kind and length of papers published in the journal, or the different forms of peer review and discussion around what is published. Tactics The length of papers published in TSE has on occasion been a topic for some discussion. I do not propose to change the policy in this area but to clarify it, as I think it hides a number of issues within it. TSE publishes papers of any length, as long as their length is appropriate for the content presented. The discussion has often centered around what to do if accepted papers are over the IEEE Computer Society’s recommended length of 15 pages. However, there is an equally interesting discussion to be had for short papers. My view is this: There is nothing sacred about the length of a software engineering research contribution. Substantial pieces of work may need lengthy and detailed accounts of techniques, or of empirical studies or other kinds of evidence; but equally valuable results may be published in short papers. Indeed, other disciplines manage to publish seminal results in four pages. I will continue to be guided by my associate editors as to what constitutes an appropriate length for any particular contribution. I believe that we, as a community, have largely won the battle of persuading our deans and managers that publishing in conferences is a respectable form of publication. However, in a world of economic difficulties, carbon footprint consciousness, and fast internet-time publication, there is a strong case to be made that we need to redress the balance and publish more of our research in journals. Indeed, I would go as far as saying that many research students now go through their entire doctoral studies publishing in workshops and conferences only, and think that all research contributions can fit into the 2-column, 10-page format of IEEE conference publications. As a result, other than their PhD dissertations, these students do not get an opportunity to publish their work in an archival journal format. Of course, the frequency of conference reviewing has also had an impact on the nature of reviews that referees are asked to write. With little scope for improving conference papers before publication and heavy referee review loads, reviews tend to be short critiques of papers, rather than substantive engagements with the content that authors are trying to present. I therefore believe that journal reviews and revision allow for better quality work to be produced incrementally and then published. Of course, the journal publication process is not without cost to authors, referees, and editors, and we need to acknowledge this and tackle it head on. I was very taken by the discussion by Crowcroft et al. [1] on the varying incentives of the different stakeholders in the publication process: authors, referees, and editors. For TSE, the kind of behavior I would like to incentivize is for authors to submit innovative, rigorous, and well-presented accounts of their research and not overload the system with half-baked ideas or very small increments on previous work. I would like to incentivize referees to agree to review papers and to produce rigorous, thoughtful reviews. And, I would like to incentivize editors to seek and encourage submission of a wider range of contributions that will serve our research and practitioner community better. I have no magic to generate these incentives. However, in a year’s time TSE will make a number of awards to authors, referees, and (associate) editors to acknowledge the quality of research, feedback, and editing. I welcome feedback from the community on the specification of such awards.

The methodologies for the development of ontologies aimed to be used as software artifacts remain to be an open research area. Although the most widely recognized are rooted on UML given the acceptance of that language in the community of software engineering, none of them are fully mature. Recent works propose the mapping of SBVR expressions to ontology statements as a building technique, but just an empirical study comparing SBVR and UML-rooted techniques has been performed until now. This work analyzes the technical feasibility of SBVR to OWL 2 mappings by depicting a first differentiated replication of the original experiment varying the treatments, the size and composition of the experimental units, and comparing the performance of SBVR and ODM-based techniques. The findings allow sustaining the technical feasibility of the SBVR to OWL 2 mappings as an ontology development technique able to be applied by the software engineering community.

Since their wide adoption by the software engineering community in the mid-90's, design patterns have become an important educational component in the training of novice software engineers due to the common belief that, as distilled experience of seasoned software designers, they can transform novice software engineers into skilled professionals in a relatively short time frame. This paper questions the validity of this commonly-held belief about the educational value of conventional patterns, arguing that although there is tremendous value in capturing and disseminating software engineering experience in the form of patterns, conventional design patterns cannot deliver on this expectation to significantly shorten the experience growth curve. We report initial results from an ongoing research project that aims to not only identify the difficulties in using conventional patterns as educational means for novices, but also to use such insights to develop new forms of patterns to help educators and experts to more effectively communicate and transfer their software engineering knowledge, experience, and understanding of best practices to novices.

Social media has changed the world and play an important role in people lives. Social media platforms like Twitter, Facebook and YouTube create a new dimension of communication by providing channels to express and exchange ideas freely. Although the evolution brings numerous benefits, the dynamic environment and the allowable of anonymous posts could expose the uglier side of humanity. Irresponsible people would abuse the freedom of speech by aggressively express opinion or idea that incites hatred. This study performs hate speech and offensive language detection. The problem of this task is there is no clear boundary between hate speech and offensive language. In this study, a selected new features set is proposed for detecting hate speech and offensive language. Using Twitter dataset, the experiments are performed by considering the combination of word n-gram and enhanced syntactic n-gram. To reduce the feature set, filter-embedded combining feature selection is used. The experimental results indicate that the combination of word n-gram and enhanced syntactic n-gram with feature selection to classify the data into three classes: hate speech, offensive language or neither could give good performance. The result reaches 91% for accuracy and the averages of precision, recall and F1.

With the tremendous growth in the complexity of software development in the last 1015 years, the management of risks in software engineering activities is becoming an important and non-trivial issue from three perspectives: project, process and product. Therefore, researchers and practitioners are continually trying to find effective risk management approaches. In this paper, we briefly discuss the principles of risk management in software engineering, review some of the process models popular in the software engineering community, and finally discuss some of the important works conducted recently in this area in the last five years. While writing the paper, we have focused mostly on project, and process-based risks and not on product risks.

There has long been a close association between research in software engineering and the design of programming languages. Part of the IMPACT project involves an exploration of the interrelations of these two fields and documentation in a report of how fundamental research in software engineering has been a valuable resource for programming language features commonly used today. The resulting report investigates the relationship by considering features in currently used languages, including exceptions, control and data abstractions, types, inheritance, concurrency and visualization mechanisms.This paper, exerpted from the report, focuses on the influence of software engineering research on the development of exceptions. The paper demonstrates that there is a symbiotic relationship between software engineering research and the design of exception handing in programming languages. Publication of these partial results is aimed at soliciting feedback and comments from both the programming languages and software engineering communities.