As new forms of propaganda and information control spread across the internet, the need for novel ways of identifying them increases as well. One increasingly popular method of spreading false messages on microblogs like Twitter is to disseminate them from seemingly ordinary, but centrally controlled and coordinated user accounts – sockpuppets. In this paper we examine a number of potential methods for identifying these by way of applying plagiarism detection algorithms for text, and evaluate their performance against this type of threat. We identify one type of algorithm in particular – that using vector space modeling of text – as particularly useful in this regard. / Allteftersom  nya  former  av  propaganda  och  informationskontroll  sprider sig över internet krävs också nya sätt att identifiera dessa. En  allt mer populär metod för att sprida falsk information på mikrobloggar  som  Twitter  är  att  göra  det  från  till  synes  ordinära,  men  centralt  kontrollerade och koordinerade användarkonton – på engelska kända  som “sockpuppets”. I denna undersökning testar vi ett antal potentiella  metoder  för  att  identifiera  dessa  genom  att  applicera  plagiatkontrollalgoritmer  ämnade  för  text,  och  utvärderar  deras prestanda mot denna sortens hot. Vi identifierar framför allt en typ av  algoritm  –  den  som  nyttjar  vektorrymdsmodellering  av  text  –  som speciellt användbar i detta avseende.

Students are rarely explicitly taught how to develop their writing within a subject discipline, as there is usually a focus on teaching content. However, academic writing, and in particular Academic Reflective Writing (ARW), is very challenging for most students. In this study, a series of three embedded writing development interventions were trailed with successive cohorts of postgraduate Nursing students writing a summative 4000 word piece of ARW. The interventions included the use of example texts to make task requirements more explicit, formative peer feedback on draft texts and facilitating increased dialogue between staff and students regarding expectations of this task. Overall the interventions represented a shift towards assessment for learning. Quantitative results showed a decrease in the number of students investigated for plagiarism, a rise in pass rates and mean grades, and an increased uptake of academic supervision over the three cohorts. In addition, complementary findings from a self-selected focus group interview indicated that respondents perceived the writing development activities to be very useful. In particular, the formative peer and tutor review of written drafts, was valued. However, a limitation of this pragmatic mixed method study was that the three cohorts were non-equivalent. Despite this, it is argued that, as ARW is so complex, disciplinary academics should embed explicit guidance and scaffolding in their teaching in order to enhance written reflection and learning. Failure to do so may lead ARW to become an exclusive educational practice leading to unintentional plagiarism and poor written reflection on practice.

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In recent years, it has been observed that software clones and plagiarism are becoming an increased threat for one?s creativity. Clones are the results of copying and using other?s work. According to the Merriam – Webster dictionary, “A clone is one that appears to be a copy of an original form”. It is synonym to duplicate. Clones lead to redundancy of codes, but not all redundant code is a clone.On basis of this background knowledge ,in order to safeguard one?s idea and to avoid intentional code duplication for pretending other?s work as if their owns, software clone detection should be emphasized more. The objective of this paper is to review the methods for clone detection and to apply those methods for finding the extent of plagiarism occurrence among the Swedish Universities in Master level computer science department and to analyze the results.The rest part of the paper, discuss about software plagiarism detection which employs data analysis technique and then statistical analysis of the results.Plagiarism is an act of stealing and passing off the idea?s and words of another person?s as one?s own. Using data analysis technique, samples(Master level computer Science thesis report) were taken from various Swedish universities and processed in Ephorus anti plagiarism software detection. Ephorus gives the percentage of plagiarism for each thesis document, from this results statistical analysis were carried out using Minitab Software.The results gives a very low percentage of Plagiarism extent among the Swedish universities, which concludes that Plagiarism is not a threat to Sweden?s standard of education in computer science.This paper is based on data analysis, intelligence techniques, EPHORUS software plagiarism detection tool and MINITAB statistical software analysis.

The work focuses on issues of plagiarism detection in large document repositories. Taking into account real situation that needs to be addressed now in the university environment in the Czech Republic and proposes a system that will be able to carry out this analysis in real time and yet be able to capture the widest possible range of plagiarism methods. The main contribution of this work is taking the definition of so-called unordered n-grams - {n}-grams - which can be used just to detect some forms of advanced plagiarism methods. All cited recommendations that relate to the various components of the system to detect plagiarism - preprocessing the document before document insertion into the corpus, the representation of documents in document storage, identification of potential sources of plagiarism to calculate rates of similarity; visualization analysis of plagiarism - are subject to discussion and appropriately quantified. The result is a set of design parameters of the system so that it can in detect plagiarism in the Czech language language quickly, accurately and yet in most forms.

The purpose of this study was to better understand how the universities in Sweden work to prevent plagiarism, how they use plagiarism detection tools and what knowledge the students have or wish to have about plagiarism. This was studied through interviews with teachers and administration staff from one smaller university in Sweden together with a questionnaire for students attending any university in Sweden. The study shows that the information about plagiarism can be clearer from teachers according to the students, to prevent plagiarism as far as possible. It also shows that the university is already working to improve the information so that the students in a better way can understand, but it is hard to know how to give the information and what information that the students need. The examined university are using the system Urkund as a plagiarism detection tool and the study shows that teachers in general are satisfied with the system and how they use it. However, some teachers see an opportunity to use the detection tool in their teaching practises but need more knowledge of the system to do so efficiently. The students reportedly know what plagiarism means according to the study, but they do not have a deeper knowledge about it which they want from their universities, especially how the school is handling plagiarism cases and how the plagiarism detection tool works. The study concludes with recommendations for the universities to improve their work against plagiarism. / Syftet med denna studie var att ta reda på hur ett lärosäte i dagsläget arbetar för att motverka plagiat, hur man använder plagiatkontrollsystem och vad studenterna har för kunskap eller vilken information de känner att de saknar gällande plagiering. Detta undersöktes genom att intervjua lärare och förvaltningsanställda på en mindre högskola i Sverige och även genom en enkätundersökning som gick ut till studenter vid högre utbildning i hela Sverige. Studien visade att många studenter upplever att informationen från lärare och lärosätet kan bli tydligare för att i största möjliga mån undvika plagieringsfall. Den visar på att lärosätet redan jobbar för att förbättra informationen för studenterna men att det är svårt att veta vad som fungerar optimalt. Studien visar också på hur systemet Urkund används och i vilken grad. De allra flesta lärarna tycker att det är ett bra och användbartsystem och det känner sig bekväma med användandet, många kan också se en möjlighet till att använda systemet på ett mer pedagogiskt vis men behöver mer kunskap i hur det skulle kunna fungera. Studenterna anser sig veta vad plagiat innebär men en stor del tycker sig sakna mer djupgående information från sitt lärosäte för att få en bättre förståelse i främst förfarande vid upptäckt av plagiat och hur plagiatkontrollsystem fungerar. Slutligen ges rekommendationer till lärosäten för att kunna utveckla sitt arbete med att motverka plagiering och förbättra kommunikationen mellan lärare och studenter för att minimera plagiatfall.

This dissertation examined how previous information literacy training, law student gender, age, and previously obtained education affects first, second, and third year law students selection of information sources, their understanding of common knowledge, and their decision of whether or not to give attribution to these sources. To examine these factors, this study implemented a paradigm called the principle of least effort that contended humans in general tended to complete the least amount of work possible to complete presented tasks. This study sought to discover whether law students follow this same path of completing the least amount of work possible to finish presented tasks, and whether this behavior affects information source selection, citation, and understanding of common knowledge. I performed six focus groups and crafted and disseminated an online survey to examine these factors. Via this data collection, it was discovered that law students do exhibit some differences in understanding of citation and citation behavior based on age and their year in law school. They also exhibited some differences regarding common knowledge based on their year in law school, where they received their information literacy training, and where they attend law school. Yet, no statistically significant differences were discovered regarding where one attends law school and citation and source selection. Further this study revealed law students do follow this paradigm and seek the path of least resistance to accomplish law school assignments.

This thesis is dealing with programming languages C and C++, various methods writing their constructions and development of application which detects very similar programs written in these languages. The application is intended to control plagiarism in school projects in which students have to create a program in C or C++. The application can check short programs as well as large programs divided into several modules.

Made available in DSpace on 2016-03-15T19:37:29Z (GMT). No. of bitstreams: 1 Evandro Luquini.pdf: 2663730 bytes, checksum: 45c13b956053ea1328342984d7ecf01c (MD5) Previous issue date: 2010-08-05 / Coordenação de Aperfeiçoamento de Pessoal de Nível Superior / The broad topic of this research is related to computer supported learning and teaching environment. In particular due to the high society´s demand for human resources capable of building and maintaining computer systems the specific topic of this research is focused on computer tools to support programming learning and teaching using techniques from social network and plagiarism detection. Currently the teachers involved with programming teaching have a set of tools to detect plagiarism of source code in the exercises and assessments made by their students. Although these tools are useful as disciplinary measures they do not allow teachers to think about plagiarism from a social perspective. This paper develops and exploits the assumption that plagiarism in the context of programming teaching does not happen in isolation from the social network formed by students in the classroom. From this formulation is suggested that the plagiarism detection algorithms and the students source code presented during the course are sufficient to model indirectly the social network established by the group of students. An exploratory experiment was conducted to evaluate this hypothesis and an intervention procedure was proposed. This procedure was inspired by immunization techniques from social networks and it has the goal to improve learning. / Este trabalho está inserido no contexto das pesquisas que procuram desenvolver ambientes computacionais que apóiam efetivamente os processos de ensino aprendizagem. Em especial, devido à grande demanda da sociedade por recursos humanos capazes de construir e manter sistemas computacionais. O tema específico desta pesquisa concentra-se na aplicação de técnicas de redes sociais e algoritmos de detecção de plágio à questão da aprendizagem de programação. Atualmente os professores envolvidos com o ensino de programação possuem um conjunto de ferramentas capazes de detectar o plágio de código-fonte nos exercícios e avaliações realizados por seus alunos. Apesar de estas ferramentas serem úteis como instrumentos disciplinadores, elas não permitem ao docente refletir sobre a natureza social do plágio. Este trabalho desenvolve e instrumentaliza a hipótese de que o plágio, no contexto do ensino de programação, não acontece isoladamente da rede social formada pelos alunos em sala de aula. Em decorrência desta formulação propõe-se que os algoritmos de detecção de plágio e os códigos fonte apresentados durante uma disciplina serão suficientes para modelar indiretamente a rede social estabelecida pelo grupo de alunos. Um experimento exploratório foi conduzido para avaliar esta hipótese e um procedimento para intervenção inspirado nas técnicas de imunização de redes sociais foi proposto com o intuito de aumentar a eficácia da aprendizagem.

The thesis describes the design and implementation of a plagiarism tool for programming languages C, Python and PHP. It describes techniques that are used to cover a plagiarism. The aim of this work is to create a tool for detection and visualization of plagiarisms covered up using these techniques. The tool performs detection by transforming input projects into an abstract syntactic tree, which is obtained by lexical and syntactic analysis. These trees will be compared by a proposed algorithm that uses node and subtree valuation using the {hash} function. The found parts of the code that could potentially lead to plagiarism are visualized in the form of a subtree of an abstract syntactic tree that represents the parts of the code found by the tool. Further, the work  describes testing of this tool on identified plagiarism techniques and specifies which of them it can eliminate. In its conclusion, the work describes the possible further development of the tool.