Social Fingerprinting: detection of spambot groups through DNA-inspired behavioral modeling

Spambot detection in online social networks is a long-lasting challenge involving the study and design of detection techniques capable of efficiently identifying ever-evolving spammers. Recently, a new wave of social spambots has emerged, with advanced human-like characteristics that allow them to go undetected even by current state-of-the-art algorithms. In this paper, we show that efficient spambots detection can be achieved via an in-depth analysis of their collective behaviors exploiting the digital DNA technique for modeling the behaviors of social network users. Inspired by its biological counterpart, in the digital DNA representation the behavioral lifetime of a digital account is encoded in a sequence of characters. Then, we define a similarity measure for such digital DNA sequences. We build upon digital DNA and the similarity between groups of users to characterize both genuine accounts and spambots. Leveraging such characterization, we design the Social Fingerprinting technique, which is able to discriminate among spambots and genuine accounts in both a supervised and an unsupervised fashion. We finally evaluate the effectiveness of Social Fingerprinting and we compare it with three state-of-the-art detection algorithms. Among the peculiarities of our approach is the possibility to apply off-the-shelf DNA analysis techniques to study online users behaviors and to efficiently rely on a limited number of lightweight account characteristics

The paradigm-shift of social spambots: Evidence, theories, and tools for the arms race

Recent studies in social media spam and automation provide anecdotal argumentation of the rise of a new generation of spambots, so-called social spambots. Here, for the first time, we extensively study this novel phenomenon on Twitter and we provide quantitative evidence that a paradigm-shift exists in spambot design. First, we measure current Twitter's capabilities of detecting the new social spambots. Later, we assess the human performance in discriminating between genuine accounts, social spambots, and traditional spambots. Then, we benchmark several state-of-the-art techniques proposed by the academic literature. Results show that neither Twitter, nor humans, nor cutting-edge applications are currently capable of accurately detecting the new social spambots. Our results call for new approaches capable of turning the tide in the fight against this raising phenomenon. We conclude by reviewing the latest literature on spambots detection and we highlight an emerging common research trend based on the analysis of collective behaviors. Insights derived from both our extensive experimental campaign and survey shed light on the most promising directions of research and lay the foundations for the arms race against the novel social spambots. Finally, to foster research on this novel phenomenon, we make publicly available to the scientific community all the datasets used in this study.Comment: To appear in Proc. 26th WWW, 2017, Companion Volume (Web Science Track, Perth, Australia, 3-7 April, 2017

Fame for sale: efficient detection of fake Twitter followers

$\textit{Fake followers}$ are those Twitter accounts specifically created to inflate the number of followers of a target account. Fake followers are dangerous for the social platform and beyond, since they may alter concepts like popularity and influence in the Twittersphere - hence impacting on economy, politics, and society. In this paper, we contribute along different dimensions. First, we review some of the most relevant existing features and rules (proposed by Academia and Media) for anomalous Twitter accounts detection. Second, we create a baseline dataset of verified human and fake follower accounts. Such baseline dataset is publicly available to the scientific community. Then, we exploit the baseline dataset to train a set of machine-learning classifiers built over the reviewed rules and features. Our results show that most of the rules proposed by Media provide unsatisfactory performance in revealing fake followers, while features proposed in the past by Academia for spam detection provide good results. Building on the most promising features, we revise the classifiers both in terms of reduction of overfitting and cost for gathering the data needed to compute the features. The final result is a novel $\textit{Class A}$ classifier, general enough to thwart overfitting, lightweight thanks to the usage of the less costly features, and still able to correctly classify more than 95% of the accounts of the original training set. We ultimately perform an information fusion-based sensitivity analysis, to assess the global sensitivity of each of the features employed by the classifier. The findings reported in this paper, other than being supported by a thorough experimental methodology and interesting on their own, also pave the way for further investigation on the novel issue of fake Twitter followers

DNA-inspired online behavioral modeling and its application to spambot detection

We propose a strikingly novel, simple, and effective approach to model online user behavior: we extract and analyze digital DNA sequences from user online actions and we use Twitter as a benchmark to test our proposal. We obtain an incisive and compact DNA-inspired characterization of user actions. Then, we apply standard DNA analysis techniques to discriminate between genuine and spambot accounts on Twitter. An experimental campaign supports our proposal, showing its effectiveness and viability. To the best of our knowledge, we are the first ones to identify and adapt DNA-inspired techniques to online user behavioral modeling. While Twitter spambot detection is a specific use case on a specific social media, our proposed methodology is platform and technology agnostic, hence paving the way for diverse behavioral characterization tasks

Effect of airborne particle abrasion on microtensile bond strength of total-etch adhesives to human dentin

Aim of this study was to investigate a specific airborne particle abrasion pretreatment on dentin and its effects on microtensile bond strengths of four commercial total-etch adhesives. Midcoronal occlusal dentin of extracted human molars was used. Teeth were randomly assigned to 4 groups according to the adhesive system used: OptiBond FL (FL), OptiBond Solo Plus (SO), Prime & Bond (PB), and Riva Bond LC (RB). Specimens from each group were further divided into two subgroups: control specimens were treated with adhesive procedures; abraded specimens were pretreated with airborne particle abrasion using 50 mu m Al2O3 before adhesion. After bonding procedures, composite crowns were incrementally built up. Specimens were sectioned perpendicular to adhesive interface to producemultiple beams, which were tested under tension until failure. Data were statistically analysed. Failure mode analysis was performed. Overall comparison showed significant increase in bond strength (p < 0.001) between abraded and no-abraded specimens, independently of brand. Intrabrand comparison showed statistical increase when abraded specimens were tested compared to no-abraded ones, with the exception of PB that did not show such difference. Distribution of failure mode was relatively uniform among all subgroups. Surface treatment by airborne particle abrasion with Al2O3 particles can increase the bond strength of total-etch adhesive

Histologic evaluation of bone healing of adjacent alveolar sockets grafted with bovine- and porcine-derived bone: a comparative case report in humans

To evaluate and compare histomorphometrically the bone response to two xenografts, one bovine and the other porcine, grafted in adjacent extraction sockets in a human. In this case report, two adjacent maxillary premolars were extracted, and the sockets were filled with two different xenogeneic bone substitutes (first premolar with bovine bone, and second premolar with porcine bone) to counteract post-extraction volume loss. Following 6 months bone core specimens were harvested during the placement of implants at the regenerated sites. Histomorphometrically, for the bovine xenograft the percentage of newly formed bone (osteoid) was 26.85%, the percentage of the residual graft material was 17.2% and the percentage of connective tissue 48.73%, while for the porcine xenograft, newly formed bone (osteoid) represented 32.19%, residual graft material was 6.57% and non-mineralized connective tissue was 52.99%. Histological results indicated that both biomaterials assessed in this study as grafts for socket preservation technique are biocompatible and osteoconductive. Bovine bone derived demonstrated to be less resorbable than porcine bone derived. Both xenogenic biomaterials did not interfere with the normal bone reparative processe

Aryl–Cl vs heteroatom–Si bond cleavage on the route to the photochemical generation of σ,π-heterodiradicals

The photochemistry of aryl chlorides having a X-SiMe3 group (X = O, NR, S, SiMe2) tethered to the aromatic ring has been investigated in detail, with the aim to generate valuable ϭ,π-heterodiradicals. Two competitive pathways arising from the excited triplet state of the aromatics have been observed, namely heterolysis of the aryl–chlorine bond and homolysis of the X–silicon bond. The former path is found in chlorinated phenols and anilines, whereas the latter is exclusive in the case of silylated thiophenols and aryl silanes. A combined experimental/computational approach was pursued to explain such a photochemical behavior. Graphical abstract[Figure not available: see fulltext.

Use of Lozenges Containing Lactobacillus brevis CD2 in Recurrent Aphthous Stomatitis: A Double-Blind Placebo-Controlled Trial

Recurrent aphthous stomatitis is a common disorder of the oral cavity, affecting mainly young people. It is characterized by small ulcers which can be very painful and generally heal spontaneously within 7–14 days. There is currently no therapy that can provide rapid healing. This study evaluated the efficacy and rapidity of response of a lozenge containing Lactobacillus brevis CD2. 30 patients were randomized to take 4 lozenges a day of active product or placebo for 7 days. Signs and symptoms as well as laboratory parameters in the saliva were assessed at the start of the study and after 7 days of treatment. The study demonstrated the efficacy and the rapidity of response of the Lactobacillus brevis CD2 lozenges in resolving the clinical signs and symptoms of aphthous stomatitis, with a significantly rapid improvement of pain. This is the first study confirming the efficacy of a probiotic product in this pathology