Automatic Detection of Cyberbullying in Social Media Text

While social media offer great communication opportunities, they also increase the vulnerability of young people to threatening situations online. Recent studies report that cyberbullying constitutes a growing problem among youngsters. Successful prevention depends on the adequate detection of potentially harmful messages and the information overload on the Web requires intelligent systems to identify potential risks automatically. The focus of this paper is on automatic cyberbullying detection in social media text by modelling posts written by bullies, victims, and bystanders of online bullying. We describe the collection and fine-grained annotation of a training corpus for English and Dutch and perform a series of binary classification experiments to determine the feasibility of automatic cyberbullying detection. We make use of linear support vector machines exploiting a rich feature set and investigate which information sources contribute the most for this particular task. Experiments on a holdout test set reveal promising results for the detection of cyberbullying-related posts. After optimisation of the hyperparameters, the classifier yields an F1-score of 64% and 61% for English and Dutch respectively, and considerably outperforms baseline systems based on keywords and word unigrams.Comment: 21 pages, 9 tables, under revie

The efficacy of bentonite and zeolite in reducing aflatoxin B1 toxicity on production performance and intestinal and hepatic health of broiler chickens

This research aimed to assess the influences of bentonite (BN) and zeolite (ZE) on reducing toxic influences of aflatoxin B1 (AFB1) in broilers by examining growth performance, carcase characteristics, serum indices, ileum morphology, apparent nutrient digestibility, and liver AFB1 residues. In total, 360 11-d-old straight-run broilers (Ross 308) were randomly allocated into 6 dietary treatments, with 10 replications of 6 birds each, in a 20-d experiment. The treatments were as follows: standard basal diet (negative control, NC); NC + 0.25 mg/kg AFB1 (positive control, PC); NC + 0.4% BN; NC + 0.4% ZE; PC + 0.4% BN; PC + 0.4% ZE. Compared to the NC diet, feeding the PC diet decreased daily feed intake (DFI) during the grower and overall periods (p < .01), reduced daily weight gain (DWG) and production efficiency factor (PEF) and increased feed conversion ratio (FCR) during grower, finisher, and overall periods (p < .001), lowered breast meat yield (p < .01), diminished dressing percentage, serum concentrations of total protein (TP), albumin (ALB), glucose (GLU), total antioxidant capacity (T-AOC), and total superoxide dismutase (T-SOD), villus height (VH), villus surface area (VSA), apparent digestibility of crude protein (CP) and ether extract (EE), apparent metabolisable energy (AME), and nitrogen-corrected AME (AMEn) (p < .001), and raised proportional liver weight, serum activities of glutamic oxaloacetic transaminase (GOT) and glutamate pyruvate transaminase (GPT), and residues of AFB1 in the liver (p < .001). Compared to the PC diet, feeding the PC + 0.4% BN or PC + 0.4% ZE diets increased DWG and PEF and decreased FCR during finisher and overall periods, raised dressing percentage, serum levels of TP, GLU, T-AOC, and T-SOD, apparent CP digestibility, and reduced proportional liver weight and AFB1 residues in the liver (p < .001). Moreover, feeding the PC + 0.4% BN diet increased VH, VSA, apparent EE digestibility, AME, and AMEn, and decreased serum GOT and GPT activities when compared to the PC diet (p < .001). Whereas, feeding the PC + 0.4% ZE diet increased DFI during all experimental periods (p < .05) and DWG and PEF during the grower period (p < .001) as compared to the PC diet. To conclude, our findings demonstrate that dietary addition of 4 g/kg BN can deliver a better safeguard against the adverse influences of AFB1 in broiler chickens

Studying the Dissemination of the K-core Influence in Twitter Cascades

Part 1: Social Media - Games - OntologiesInternational audienceThe k-core of an information graph is a common measure of a node connectedness in diverse applications. The k-core decomposition algorithm categorizes nodes into k-shells based on their connectivity. Previous research claimed that the super-spreaders are those located on the k-core of a social graph and the nodes become of less importance as they get assigned to a k-shell away from the k-core. We aim to evaluate the influence span of the social media super-spreaders, located at the k-core, in terms of the number of k-shells that their influence can reach. We base our methodology on the observation that the k-core size is directly correlated to the graph size under certain conditions. We explain these conditions and then investigate it further on real-life meme cascades extracted from Twitter. We utilize the correlation to assess the effectiveness of the k-core nodes for influence dissemination. The results of the carried-out experiments show that the correlation exists in our studied real-life datasets. A high correlation existed between the k-core size and the sizes of the inner k-shells in all the examined datasets. However, the correlation starts to decrease in the outer k-shells. Further investigations have shown that the k-shells that were less correlated exhibited a higher presence of spam accounts

The Tweet Advantage: An Empirical Analysis of 0-Day Vulnerability Information Shared on Twitter

Part 3: Secuirty Management / ForensicInternational audienceIn the last couple of years, the number of software vulnerabilities and corresponding incidents increased significantly. In order to stay up-to-date about these new emerging threats, organizations have demonstrated an increased willingness to exchange information and knowledge about vulnerabilities, threats, incidents and countermeasures. Apart from dedicated sharing platforms or databases, information on vulnerabilities is frequently shared on Twitter and other social media platforms. So far, little is known about the obtainable time advantage of vulnerability information shared on social media platforms. To close this gap, we identified 709,880 relevant Tweets and subsequently analyzed them. We found that information with high relevance for affected organizations is shared on Twitter often long before any official announcement or patch has been made available by vendors. Twitter is used as a crowdsourcing platform by security experts aggregating vulnerability information and referencing a multitude of public available webpages in their Tweets. Vulnerability information shared on Twitter can improve organizations reaction to newly discovered vulnerabilities and therefore help mitigating threats