Search results

This paper aims to investigate how congruent keywords are used in information security policies (ISPs) to pinpoint and guide clear actionable advice and suggest a metric for measuring the quality of keyword use in ISPs.

A qualitative content analysis of 15 ISPs from public agencies in Sweden was conducted with the aid of Orange Data Mining Software. The authors extracted 890 sentences from these ISPs that included one or more of the analyzed keywords. These sentences were analyzed using the new metric – keyword loss of specificity – to assess to what extent the selected keywords were used for pinpointing and guiding actionable advice. Thus, the authors classified the extracted sentences as either actionable advice or other information, depending on the type of information conveyed.

The results show a significant keyword loss of specificity in relation to pieces of actionable advice in ISPs provided by Swedish public agencies. About two-thirds of the sentences in which the analyzed keywords were used focused on information other than actionable advice. Such dual use of keywords reduces the possibility of pinpointing and communicating clear, actionable advice.

The suggested metric provides a means to assess the quality of how keywords are used in ISPs for different purposes. The results show that more research is needed on how keywords are used in ISPs.

The authors recommended that ISP designers exercise caution when using keywords in ISPs and maintain coherency in their use of keywords. ISP designers can use the suggested metrics to assess the quality of actionable advice in their ISPs.

The keyword loss of specificity metric adds to the few quantitative metrics available to assess ISP quality. To the best of the authors’ knowledge, applying this metric is a first attempt to measure the quality of actionable advice in ISPs.

Drug sales facilitated through digital communication on the surface web and on darknet cryptomarkets have increased during the past two decades. This has resulted in an increase in drug law enforcement efforts to combat these markets and a subsequent increase in judicial sentencing of people selling drugs online. The aim of this study was to analyze how Swedish courts describe sentenced sellers and how the courts apply case law.

The empirical material consists of 71 sentencing documents produced by Swedish courts in cases of online drug selling between January 1, 2010 and January 1, 2020. In total, 99 sentenced persons occur in the documents. Using a qualitative research design, the authors analyzed the material through thematic text analysis.

Overall, in their descriptions of online drug sale operations, the courts’ characterizations of the concepts of street capital and digital capital show a dichotomy. These forms of capital are situationally described as both aggravating and mitigating aspects in the application of case law, indicating that it may be fruitful to view both street and digital capital as resources used on contemporary drug markets in general.

Very little research exists into how judicial systems describe and perceive the developing phenomenon of online drug sales. Using a relatively large sample from a decade of sentencing, the authors provide an analysis of how Swedish courts view and valuate capital forms in the online drugs trade.

Over a decade since the Special Criminal Court (SCC) was established in Cameroon, hundreds of individuals have been indicted, tried and convicted. Sentences have been imposed, most of which include a term of imprisonment (principal punishment/penalty) and confiscation as accessory penalty or punishment. Research focus has not been directed at the sentences which, as argued in this paper, are inconsistent, incommensurate with the amounts of money stolen and a significant departure from the Penal Code. This paper aims to explore the aspect of sentencing by the SCC.

To identify, highlight and discuss the issue of sentencing, the paper looks at a blend of primary and secondary materials: primary materials here include but not limited to the judgements of the SCC and other courts in Cameroon and the Penal Code. Secondary materials shall include the works of scholars in the fields of criminal law, criminal justice and penal reform.

A few findings were made: first, the judges are inconsistent in the manner in which they determine the appropriate sentence. Second, in making that determination, the judges would have been oblivious to the prescripts in the Penal Code, which provides the term of imprisonment, and in the event of a mitigating circumstance, the prescribed minimum to be applied. Yet, the default imposition of an aggravating circumstance (being a civil servant) was not explored by the SCC. Finally, whether the sentences imposed are commensurate with the amounts of monies stolen.

This research unravels key insights into the functioning of the SCC. It advances the knowledge thereon and adds to the literature on corruption in Cameroon.

The prosecution and judges at the SCC should deepen their knowledge of Cameroonian criminal law, especially on the nature of liberty given to judges to determine within the prescribed range of the sentence to be imposed but also consider the existence of an aggravating factor – civil servant. They must also consider whether the sentences imposed befit the crime for which they are convicted.

The paper is an original contribution with new insights on the manner in which sentencing should be approached by the SCC.

Canada criminalized the nonconsensual distribution of intimate images in 2014. Lawmakers and commentators noted that this new offense would fill a legislative gap in relation to “revenge pornography,” which entails individuals (typically men) sharing intimate images of their ex-partners (typically women) online in an attempt to seek revenge or cause them harm. Feminist writers and activists categorize revenge pornography as a symptom and consequence of “rape culture,” in which sexual violence is routinely trivialized and viewed as acceptable or entertaining, and women are blamed for their sexual victimization. In this chapter, I analyze Canada's burgeoning revenge pornography case law and find that these cases support an understanding of revenge pornography as a serious form of communal, gendered, intimate partner violence, which is extremely effective at harming victims because of broader rape culture. While Canadian judges are taking revenge pornography seriously, there is some indication from the case law that they are at risk of relying on gendered reasoning and assumptions previously observed by feminists in sexual assault jurisprudence, which may have the result of bolstering rape culture, rather than contesting it.

The framework of this paper is financial mathematics and, more specifically, the control of data fraud and manipulation with their subsequent economic effects, namely, in financial markets. The purpose of this paper is to calculate the global loss or gain, which supposes, for the borrower, a change of the interest rate while the contracted loan is in force or, in another case, the loan has finished.

The methodology used in this work has been, in the first place, a review of the existing literature on the topic of manipulability and abusiveness of the loan interest rates applied by banks; in the second place, the introduction of a mathematical-financial analysis to calculate the interests paid in excess; and, finally, the compilation of several sentences issued on the application of the so-called mortgage loan reference index (MLRI) to mortgage loans in Spain.

There are three main contributions in this paper. First, the calculation of the interests paid in excess in the amortization of mortgage loans referenced to an overvalued interest rate. Second, an empirical application shows the amount to be refunded to a Spanish consumer when amortizing his/her mortgage loan referenced to the MLRI instead of the Euro InterBank Offered Rate (EURIBOR). Third, consideration has been made to the effects and the possible solutions to the legal problems arising from this type of contract.

This research is a useful tool capable of implementing the financial calculation needed to find out overpaid interests in mortgage loans and to execute the sentences dealing with this topic. However, a limitation of this study is the lack of enough sentences on mortgage loans referenced to the MLRI to get some additional information about the number of borrowers affected by these legal sentences and the amount refunded by the financial institutions.

To the best of the authors’ knowledge, this is the first time that deviations in the payment of interests have been calculated when amortizing a mortgage.

The authors constructed an automatic essay scoring (AES) model in a discussion forum where the result was compared with scores given by human evaluators. This research proposes essay scoring, which is conducted through two parameters, semantic and keyword similarities, using a SentenceTransformers pre-trained model that can construct the highest vector embedding. Combining these models is used to optimize the model with increasing accuracy.

The development of the model in the study is divided into seven stages: (1) data collection, (2) pre-processing data, (3) selected pre-trained SentenceTransformers model, (4) semantic similarity (sentence pair), (5) keyword similarity, (6) calculate final score and (7) evaluating model.

The multilingual paraphrase-multilingual-MiniLM-L12-v2 and distilbert-base-multilingual-cased-v1 models got the highest scores from comparisons of 11 pre-trained multilingual models of SentenceTransformers with Indonesian data (Dhini and Girsang, 2023). Both multilingual models were adopted in this study. A combination of two parameters is obtained by comparing the response of the keyword extraction responses with the rubric keywords. Based on the experimental results, proposing a combination can increase the evaluation results by 0.2.

This study uses discussion forum data from the general biology course in online learning at the open university for the 2020.2 and 2021.2 semesters. Forum discussion ratings are still manual. In this survey, the authors created a model that automatically calculates the value of discussion forums, which are essays based on the lecturer's answers moreover rubrics.

The purpose of this paper is to explore the prevalence of potential problem gambling among Finnish prisoners; the associations between problem gambling and demographics, substance use and crime-related factors; and problem gamblers’ support preferences.

Prisoners (n=96) from two Finnish prisons were recruited between December 2017 and January 2018. The estimated response rate was 31 percent. Gambling problems were measured using the Brief Biosocial Gambling Screen. The participants were asked to report their gambling both for one year prior to their incarceration and for the past year. The independent variables were demographics (age, gender and marital status), substance use (alcohol, smoking and narcotics) and crime-related factors (crime type, prison type and previous sentence). Statistical significance (p) was determined using Fischer’s exact test.

Past-year pre-conviction problem gambling prevalence was 16.3 percent and past-year prevalence 15 percent. Age, gender, smoking, alcohol or illicit drug use were not associated with past-year problem gambling before sentencing. One-third of the prisoners (33.3 percent) who were sentenced for a property crime, financial crime or robbery were problem gamblers. One-quarter (24 percent) of all participants showed an interest in receiving support by identifying one or more support preferences. The most preferred type of support was group support in its all forms.

It is recommended that correctional institutions undertake systematic screening for potential problem gambling, and implement tailored intervention programs for inmates with gambling problems.

This study provides a deeper understanding of problem gambling in prisons. Problem gambling is associated with crime and also seems to be linked with serving a previous sentence. Early detection and tailored interventions for problem gambling may help to reduce reoffending rates.

This paper aims to extract the comment targets in Chinese online shopping platform.

The authors first collect the comment texts, word segmentation, part-of-speech (POS) tagging and extracted feature words twice. Then they cluster the evaluation sentence and find the association rules between the evaluation words and the evaluation object. At the same time, they establish the association rule table. Finally, the authors can mine the evaluation object of comment sentence according to the evaluation word and the association rule table. At last, they obtain comment data from Taobao and demonstrate that the method proposed in this paper is effective by experiment.

The extracting comment target method the authors proposed in this paper is effective.

First, the study object of extracting implicit features is review clauses, and not considering the context information, which may affect the accuracy of the feature excavation to a certain degree. Second, when extracting feature words, the low-frequency feature words are not considered, but some low-frequency feature words also contain effective information.

Because of the mass online reviews data, reading every comment one by one is impossible. Therefore, it is important that research on handling product comments and present useful or interest comments for clients.

The extracting comment target method the authors proposed in this paper is effective.

Recently, more data-driven approaches are demanding multilingual parallel resources primarily in the cross-language studies. To meet these demands, building multilingual parallel corpora are becoming the focus of many Natural Language Processing (NLP) scientific groups. Unlike monolingual corpora, the number of available multilingual parallel corpora is limited. In this paper, the MulTed, a corpus of subtitles extracted from TEDx talks is introduced. It is multilingual, Part of Speech (PoS) tagged, and bilingually sentence-aligned with English as a pivot language. This corpus is designed for many NLP applications, where the sentence-alignment, the PoS tagging, and the size of corpora are influential such as statistical machine translation, language recognition, and bilingual dictionary generation. Currently, the corpus has subtitles that cover 1100 talks available in over 100 languages. The subtitles are classified based on a variety of topics such as Business, Education, and Sport. Regarding the PoS tagging, the Treetagger, a language-independent PoS tagger, is used; then, to make the PoS tagging maximally useful, a mapping process to a universal common tagset is performed. Finally, we believe that making the MulTed corpus available for a public use can be a significant contribution to the literature of NLP and corpus linguistics, especially for under-resourced languages.