An unsupervised method for social network spammer detection based on user information interests

Online Social Networks (OSNs) are a popular platform for communication and collaboration. Spammers are highly active in OSNs. Uncovering spammers has become one of the most challenging problems in OSNs. Classification-based supervised approaches are the most commonly used method for detecting spammers. Classification-based systems suffer from limitations of “data labelling”, “spam drift”, “imbalanced datasets” and “data fabrication”. These limitations effect the accuracy of a classifier’s detection. An unsupervised approach does not require labelled datasets. We aim to address the limitation of data labelling and spam drifting through an unsupervised approach.We present a pure unsupervised approach for spammer detection based on the peer acceptance of a user in a social network to distinguish spammers from genuine users. The peer acceptance of a user to another user is calculated based on common shared interests over multiple shared topics between the two users. The main contribution of this paper is the introduction of a pure unsupervised spammer detection approach based on users’ peer acceptance. Our approach does not require labelled training datasets. While it does not better the accuracy of supervised classification-based approaches, our approach has become a successful alternative for traditional classifiers for spam detection by achieving an accuracy of 96.9%.

A New Case of Scientific Dishonesty in the Field of Parapsychology

The present article informs about a case of prolonged scientific dishonesty in the field of parapsychology. It emerged that Alejandro Parra, an active member of the parapsychological community since about three decades, has published substantially plagiarized books and articles since at least 2007. Currently, I am aware of 20 publications that contain plagiarized sections or consist almost entirely of plagiarism. In the following, I present striking examples of such plagiarized texts and provide background information about the development of this case. Parra even presented research results obtained by others as his own research results, which amounts to data fabrication. Therefore, I conclude one cannot trust any of his books and articles. Even Parra’s publications that contain data obtained in surveys or experimental studies must be disregarded by the scientific community unless the validity of their raw data has been very carefully established by examinations performed by others.

Unsupervised Spammer Detection in Social Networks based on User Information Interests

Online Social Networks (OSNs) are a popular platform for communication and collaboration. Spammers are highly active in OSNs. Uncovering spammers has become one of the most challenging problems in OSNs. Classification-based supervised approaches are the most commonly used method for detecting spammers. The classification-based systems suffer from limitations of “data labelling”, “spam drift”, “imbalanced datasets” and “data fabrication”. These limitations effect the accuracy of a classifier’s detection. We present a pure unsupervised approach for spammer detection based on peer acceptance of a user in a social network to distinguish spammers from genuine users. The peer acceptance of a user to another user is calculated based on common shared interests over multiple shared topics between the two users. The main contribution of this paper is the introduction of a pure unsupervised spammer detection approach based on users’ peer acceptance. Our approach does not require labelled training datasets. While it does not better the accuracy of supervised classification-based approaches, our approach has become a successful alternative for traditional classifiers for spam detection by achieving an accuracy of 96.9%.

Czy (i komu) potrzebne są czasopisma naukowe? Kontekst nauk społecznych

Badacze zajmują się: (1) prowadzeniem badań naukowych oraz (2) upowszechnianiem ich wyników. Badacze zatrudnieni na uniwersytetach podejmują jeszcze dodatkową aktywność – (3) przekazują intersubiektywną wiedzę naukową (sprawdzone teorie i metody pozyskiwania tej wiedzy) swoim studentom i młodym badaczom, przygotowującym pod ich kierunkiem dysertacje doktorskie. Głównym kanałem przekazywania naukowych treści (wypełnianie przez badaczy obowiązku poddawania społecznej kontroli wytworów ich umysłów) są czasopisma naukowe. Tak jest w matematyce, fizyce, chemii, biologii, naukach medycznych czy w naukach inżynierskich. Tak też – w interesujących autora naukach społecznych – jest w psychologii. Z kolei w naukach humanistycznych (filozofia, historia, literaturoznawstwo itp.) duże znaczenie przypisuje się monografiom naukowym. Autor rozpatruje problem publikowania osiągnięć naukowych badaczy z obszaru nauk społecznych (ale jego rozważania mają też znaczenie dla klasycznych nauk humanistycznych) w czasopismach i w monografiach na tle dokonanych w Polsce – jego zdaniem - nieudolnie i bez należytego poszanowania tradycji, reform w obszarze nauki i szkolnictwa wyższego (tzw. ustawa Jarosława Gowina, ministra ds. nauki szkolnictwa wyższego, autoryzującego krytykowaną ustawę). Autor krytycznie odnosi się do negatywnych konsekwencji społecznych – zwłaszcza dla rozwoju nauki i studiów wyższych w Polsce. Autor krytycznie odnosi się do: (1) uznaniowego (bez racjonalnego uzasadnienia!) wyróżnienia listy wydawców książek naukowych, (2) stworzenia, bez należytej wnikliwości, listy czasopism. Te dwa wykazy stanowią podstawę do przeprowadzanych ewaluacji dorobku naukowego instytucji naukowych i pojedynczych badaczy. To nie mogą być rzetelne oceny. Zdaniem autora przeliczanie publikacji na punkty prowadzi do zjawiska depersonalizacji ocen osiągnięć naukowych (w wymiarze indywidualnym i instytucjonalnym). Prowadzi też do udziału, zwłaszcza młodych badaczy, w „wyścigu szczurów” (formuła: Publish or Perish) oraz rodzi zjawiska patologiczne w nauce: ghostwriting, guest authorship, plagiarism, self-plagiarism, falsification of data, fabrication of data, publikowanie w predatory journals, publication bias. Środkiem zaradczym może być tylko odejście od „punktowania” publikacji i dokonywanie ocen metodą peer review.

Korean court cases regarding research and publication ethics from 2009 to 2020

Research and publication misconduct may occur in various forms, including author misrepresentation, plagiarism, and data fabrication. Research and publication ethics are essentially not legal duties, but ethical obligations. In reality, however, legal disputes arise over whether research and publication ethics have been violated. Thus, in many cases, misconduct in research and publication is determined in the courts. This article presents noteworthy legal cases in Korea regarding research and publication ethics to help editors and authors prevent ethical misconduct. Legal cases from 2009 to 2020 were collected from the database of the Supreme Court of Korea in December 2020. These court cases represent three case types: 1) civil cases, such as affirmation of nullity of dismissal and damages; 2) criminal cases, such as fraud, interference with business, and violations of copyright law; and 3) administrative cases related to disciplinary measures against professors affiliated with a university. These cases show that although research and publication ethics are ethical norms that are autonomously established by the relevant academic societies, they become a criterion for case resolution in legal disputes where research and publication misconduct is at issue.

Public Deception as Ideological and Institutional Critique: On the Limits and Possibilities of Academic Hoaxing

Background Through an exploration of two influential academic hoaxes, the Sokal Affair and the “Grievance Studies” hoax, this article explores the constraints and possibilities of academic hoaxing in the articulation of institutional critique through a discussion of academic integrity and ethical forms of deception.Analysis In this article, hoaxes are cast as operating on a continuum with other covert forms of deception in academic publishing (fraud, data fabrication, misconduct). Far from producing constructive outcomes, these interventions serve as flashpoints for stirring up disciplinebased anxieties and ideologically motivated attacks.Conclusion and implications These forms of public deception can illuminate how to reform or re-envision areas of academia that are compromising the health and vitality of academic research. Contexte À partir d’une étude de deux importants canulars universitaires—l’affaire Sokal (1996) et le canular «grievance studies» (2018)—cet article explore les contraintes et les possibilités du canular universitaire comme forme de critique institutionnelle à travers une discussion sur l’intégrité des chercheurs et l’éthique de l’imposture.Analyse Dans cet essai, les canulars rentrent dans la même catégorie que les fraudes dans l’édition universitaire (fabrication de données, inconduite, fraude). Loin de produire des résultats constructifs, ces interventions servent de foyer pour attiser des conflits entre les disciplines et favorisent des attaques idéologiques.Conclusion et implications Ces formes d’impostures publiques peuvent révéler des façons de réformer ou de revoir certains aspects du monde universitaire qui compromettent la santé et la vitalité du milieu de la recherche.

Fraud and Misconduct in Publishing Medical Research

One of the important feature of scientific research is scrutinizing truth. Investigators strive for honesty and integrity in all scientific communications. Candidly reported methods and procedures, data and results, and their publication status should reflect authenticity. Publication of fake data diverts the search from truth. The aim of studying human subjects should be advancing research and scholarship and not just the researcher’s own career. Misconduct in medical research is any intentional deviation from acceptable ethical principles. Intentional misconduct is a serious observation, and misconduct such as falsification and fabrication of data and plagiarism are the most common fraud practices in medical research. Misconduct can occur at any stage of the research process; however, it particularly occurs in the results section of the research as researchers try to avoid negative findings. Data falsification occurs when investigators attempt to alter data to meet their own expectations. Falsification could involve altering data and results on research participants’ record to fit research report. Data fabrication occurs when researchers report data that were completely constructed and never occurred when running the research. Plagiarism is using—either deliberate or inattentive—other researchers’ ideas and words without clearly acknowledging the source of that information. Although fraud and misconduct have serious consequences, they are not uncommon among research publications in scientific journals. Institutions have to develop a mechanism to discover research misconduct and to prevent it. Editors and reviewers are required to introduce some commentaries in the regulations to impose sanctions on those found guilty of research misconduct. Key words: research, fraud, misconduct