Semantic Analysis on the Police Lingo in the Narratives of Students of Bachelor of Science in Law Enforcement Administration: A Forensic Linguistic Study

This study looks into the terminologies (police lingo) in the write-ups of Bachelor of Science in Law Enforcement Administration fourth-year students to illustrate the categorical and descriptive meanings of the words used in the narratives, identify the errors in the usage, and find out inaccuracies in the application of mechanics of writing like correct spelling, capitalization, abbreviation, and punctuation marks. Twenty-six (26) (BSLEAD) students participated in this study. They were instructed to write a narrative report in one of their experiences in the field. Police lingo identified in the statements such as nouns, verbs, and adjectives, were singled out from the narratives. These words were analyzed to determine whether they clearly stated their intention and described vividly what they meant to say. Semantic analysis was done by giving the dictionary definition of the word in the first level (categorical meaning as to parts of speech) and the illustrative meaning of the word in the second analysis (descriptive meaning), hence, the police lingo in the narratives were explained and described as to their literal meanings and clarity of intention as used in the statements. Results showed that male and female respondents have a similar choice of police lingo in writing the context of utterances in the narrative reports. They also committed errors in writing mechanics such as punctuation, spelling, and capitalization. It is recommended that the BSLEAD students engage in language learning activities like conversation using English, reading forensic texts, and listening/watching investigative programs on the radio or television that use English as a medium

Graph-based reasoning in collaborative knowledge management for industrial maintenance

Capitalization and sharing of lessons learned play an essential role in managing the activities of industrial systems. This is particularly the case for the maintenance management, especially for distributed systems often associated with collaborative decision-making systems. Our contribution focuses on the formalization of the expert knowledge required for maintenance actors that will easily engage support tools to accomplish their missions in collaborative frameworks. To do this, we use the conceptual graphs formalism with their reasoning operations for the comparison and integration of several conceptual graph rules corresponding to different viewpoint of experts. The proposed approach is applied to a case study focusing on the maintenance management of a rotary machinery system

Middle School Science Teachers\u27 Vulnerability in the Written Discourse of a Professional Learning Community

Vulnerability is omnipresent in personal and professional human experiences (Gilson, 2011; Lasky, 2005) and an unavoidable condition of work as a teacher (Bullough, 2005; Kelchtermans, 1996). It plays a role in teachers’ interaction with themselves, their students, and their professional communities, as they engage in making sense of their role in these social environments (Uitto, Kaunisto, Kelchtermans, & Estola, 2016). This study examined the written reflection journals by 12 middle school science teachers in a professional learning community (PLC) in New England. Teachers engaged with each other to co-construct knowledge and emotional understanding of their practice within this professional community. By examining teachers’ expressions in the discourse of their written reflections, vulnerability was brought to the forefront as a situated, relational way in which we open ourselves up by breaking from the expected norms of the space and outcomes of sharing. There was no existing method for analyzing vulnerability in this context therefore, the project also addressed the development of methodological processes in educational research focusing on vulnerability. Hufnagel & Kelly’s (2018) methodological considerations for examining emotional expressions informed the process along with conceptualizations of vulnerability. By examining the subject (aboutness) and discursive features of teachers’ expressions of vulnerability it was made salient what teachers’ expressed vulnerability about and the ways in which they did so. Previously, orientations to vulnerability across all disciplines have been toward minimization, rather than leveraging its necessity and importance in human connection (Gilson, 2011). While this thesis progressed research on vulnerability in education, it remains important to expand the spaces within which we have examined vulnerability to both develop and expand conceptualizations of teachers’ professional experiences and the ways in which we can support them

Learning from Corporate Memory and Best Practices

International audienc

Information Extraction in Illicit Domains

Extracting useful entities and attribute values from illicit domains such as human trafficking is a challenging problem with the potential for widespread social impact. Such domains employ atypical language models, have `long tails' and suffer from the problem of concept drift. In this paper, we propose a lightweight, feature-agnostic Information Extraction (IE) paradigm specifically designed for such domains. Our approach uses raw, unlabeled text from an initial corpus, and a few (12-120) seed annotations per domain-specific attribute, to learn robust IE models for unobserved pages and websites. Empirically, we demonstrate that our approach can outperform feature-centric Conditional Random Field baselines by over 18\% F-Measure on five annotated sets of real-world human trafficking datasets in both low-supervision and high-supervision settings. We also show that our approach is demonstrably robust to concept drift, and can be efficiently bootstrapped even in a serial computing environment.Comment: 10 pages, ACM WWW 201

Knowledge graph-based method for solutions detection and evaluation in an online problem-solving community

Online communities are a real medium for human experiences sharing. They contain rich knowledge of lived situations and experiences that can be used to support decision-making process and problem-solving. This work presents an approach for extracting, representing, and evaluating components of problem-solving knowledge shared in online communities. Few studies have tackled the issue of knowledge extraction and its usefulness evaluation in online communities. In this study, we propose a new approach to detect and evaluate best solutions to problems discussed by members of online communities. Our approach is based on knowledge graph technology and graphs theory enabling the representation of knowledge shared by the community and facilitating its reuse. Our process of problem-solving knowledge extraction in online communities (PSKEOC) consists of three phases: problems and solutions detection and classification, knowledge graph constitution and finally best solutions evaluation. The experimental results are compared to the World Health Organization (WHO) model chapter about Infant and young child feeding and show that our approach succeed to extract and reveal important problem-solving knowledge contained in online community’s conversations. Our proposed approach leads to the construction of an experiential knowledge graph as a representation of the constructed knowledge base in the community studied in this paper

Lei students’ awareness when using syntax in the writing process

"The purpose of this investigation is to study the students’ use of syntax and their awareness of it when writing in English as well as examine the different abilities the participants often practiced in Target Language V such as reading, listening, speaking, writing and if they worked with grammar. This paper will describe the methodology used to carry out this research which followed a qualitative approach. Questionnaires, researchers’ observations were used to collect data and a summary explains the findings at the end. Observations’ purpose was to know which skills were more developed during participants’ attendance to class (Target Language V); a questionnaire was applied to know students’ conceptions about syntax and if they are aware of using it when writing; finally, a data analysis to find out about participants’ performance in writing within Target Language V course"

Detecting Popularity of Ideas and Individuals in Online Community

Research in the last decade has prioritized the effects of online texts and online behaviors on user information prediction. However, the previous research overlooks the overall meaning of online texts and more detailed features about users’ online behaviors. The purpose of the research is to detect the adopted ideas, the popularity of ideas, and the popularity of individuals by identifying the overall meaning of online texts and the centrality features based on user’s online interactions within an online community. To gain insights into the research questions, the online discussions on MyStarbucksIdea website is examined in this research. MyStarbucksIdea had launched since 2008 that encouraged people to submit new ideas for improving Starbuck’s products and services. Starbucks had adopted hundreds of ideas from this crowdsourcing platform. Based on the example of the MyStarbucksIdea community, a new document representation approach, Doc2Vec, synthesized with the users’ centrality features was unitized in this research. Additionally, it also is essential to study the surface-level features of online texts, the sentiment features of online texts, and the features of users’ online behaviors to determine the idea adoption as well as the popularity of ideas and individuals in the online community. Furthermore, supervised machine learning approaches, including Logistic Regression, Support Vector Machine, and Random Forest, with the adjustments for the imbalanced classes, served as the classifiers for the experiments. The results of the experiments showed that the classifications of the idea adoption, the popularity of ideas, and the popularity of individuals were all considered successful. The overall meaning of idea texts and user’s centrality features were most accurate in detecting the adopted ideas and the popularity of ideas. The overall meaning of idea texts and the features of users’ online behaviors were most accurate in detecting the popularity of individuals. These results are in accord with the results of the previous studies, which used behavioral and textual features to predict user information and enhance the previous studies\u27 results by providing the new document embedding approach and the centrality features. The models used in this research can become a much-needed tool for the popularity predictions of future research

Applying corpus and computational methods to loanword research : new approaches to Anglicisms in Spanish

Understanding both the linguistic and social roles of loanwords is becoming more relevant as globalization has brought loanwords into new settings, often previously viewed as monolingual. Their occurrence has the potential to impact speech communities, in that they have the capacity to alter the semantic relationships and social values ascribed to individual elements within the existing lexicon. In order to identify broad patterns, we must turn towards large and varied sources of data, specifically corpora. This dissertation aims to tackle some of the practical issues involved in the use of corpora, while addressing two conceptual issues in the field of loanword research – the social distribution and semantic nature of loanwords. In this dissertation, I propose two methods, adapted from advances in computational linguistics, which will contribute to two different stages of loanword research: processing corpora to find tokens of interest and semantically analyzing tokens of interest. These methods will be employed in two case studies. The first seeks to explore the social stratification of loanwords in Argentine Spanish. The second measures the semantic specificity of loanwords relative to their native equivalents.Spanish and Portugues