Dense vs. Sparse representations for news stream clustering

The abundance of news being generated on a daily basis has made it hard, if not impossible, to monitor all news developments. Thus, there is an increasing need for accurate tools that can organize the news for easier exploration. Typically, this means clustering the news stream, and then connecting the clusters into story lines. Here, we focus on the clustering step, using a local topic graph and a community detection algorithm. Traditionally, news clustering was done using sparse vector representations with TF\u2013IDF weighting, but more recently dense representations have emerged as a popular alternative. Here, we compare these two representations, as well as combinations thereof. The evaluation results on a standard dataset show a sizeable improvement over the state of the art both for the standard F1 as well as for a BCubed version thereof, which we argue is more suitable for the task

Qlusty: Quick and dirty generation of event videos from written media coverage

Qlusty generates videos describing the coverage of the same event by different news outlets automatically. Throughout four modules it identifies events, de-duplicates notes, ranks according to coverage, and queries for images to generate an overview video. In this manuscript we present our preliminary models, including quantitative evaluations of the former two and a qualitative analysis of the latter two. The results show the potential for achieving our main aim: contributing in breaking the information bubble, so common in the current news landscape

Modelling the kinetics of Listeria monocytogenes in refrigerated fresh beef under different packaging atmospheres

The objective of this study was to model the fate of Listeria monocytogenes inoculated in beef at two concentrations (2.5 and 4.0 log CFU/g), packaged under air, vacuum and three modified atmospheres MAP: 70%O 2 /20%CO 2 /10%N 2 , 50%O 2 /40%CO 2 /10%N 2 and 30%O 2 /60%CO 2 /10%N 2 , and refrigerated at a normal temperature (4 °C) and at a mild abusive temperature (9 °C). The experimental design produced a total of 20 environmental conditions. An omnibus model based on the Weibull equation proved statistically that L. monocytogenes survives better in vacuum (VP) than in aerobic conditions, although without significant difference in its ability to survive in the temperature range between 4 °C and 9 °C. Furthermore, regardless of the refrigeration temperature, the presence of CO 2 in the package atmosphere exerted a bactericidal effect on L. monocytogenes cells, being approximately 1.5 log of reduction when storage time reached 10 days. Since the pathogen can survive in VP/MAP beef, there is a need of maintaining its numbers below 100 CFU/g before packaging by placing efforts on the implementation of control measures during processing.The authors would like to thank CECAV-UTAD and the research is supported by national funds by FCT- Portuguese Foundation for Science and Technology, under the PEst-OE/AGR/UI0772/2014. Dr. Gonzales–Barron wishes to acknowledge the financial support provided by the Portuguese Foundation for Science and Technology (FCT) through the award of a five-year Investigator Fellowship (IF) in the mode of Development Grants (IF/00570).info:eu-repo/semantics/publishedVersio

Prta: A System to Support the Analysis of Propaganda Techniques in the News

Recent events, such as the 2016 US Presidential Campaign, Brexit and the COVID-19 "infodemic", have brought into the spotlight the dangers of online disinformation. There has been a lot of research focusing on fact-checking and disinformation detection. However, little attention has been paid to the specific rhetorical and psychological techniques used to convey propaganda messages. Revealing the use of such techniques can help promote media literacy and critical thinking, and eventually contribute to limiting the impact of "fake news" and disinformation campaigns.Prta (Propaganda Persuasion Techniques Analyzer) allows users to explore the articles crawled on a regular basis by highlighting the spans in which propaganda techniques occur and to compare them on the basis of their use of propaganda techniques. The system further reports statistics about the use of such techniques, overall and over time, or according to filtering criteria specified by the user based on time interval, keywords, and/or political orientation of the media. Moreover, it allows users to analyze any text or URL through a dedicated interface or via an API. The system is available online: https://www.tanbih.org/prta

A Survey on Computational Propaganda Detection

Propaganda campaigns aim at influencing people's mindset with the purpose of advancing a specific agenda. They exploit the anonymity of the Internet, the micro-profiling ability of social networks, and the ease of automatically creating and managing coordinated networks of accounts, to reach millions of social network users with persuasive messages, specifically targeted to topics each individual user is sensitive to, and ultimately influencing the outcome on a targeted issue. In this survey, we review the state of the art on computational propaganda detection from the perspective of Natural Language Processing and Network Analysis, arguing about the need for combined efforts between these communities. We further discuss current challenges and future research directions.Comment: propaganda detection, disinformation, misinformation, fake news, media bia

Comportamento de bactérias deteriorantes e Salmonella enterica subespécie entérica O:4,5 em carne bovina embalada a vácuo durante refrigeração

In this study, the kinetic parameters of mesophilic, psychrotrophic and lactic acid bacteria in vacuum-packed beef at 1 °C and 4 °C were estimated from experimental growth curves produced by samples stored during 21 and 60 days, respectively. In a separate experiment, the survival of multidrug resistant (MDR) Salmonella enterica O:4,5 at 1°C was also characterized. The shelf-life of vacuum-packed beef stored at 4 °C was estimated at 16.1 days (95% CI: 14.8 – 17.3 days), whereas at 1 °C it was longer than 21 days because the mesophiles count estimated towards the end of the experiment was 12.5 ln CFU.g-1 (95% CI: 11.8 – 13.3 ln CFU.g-1) which is lower than the shelf-life reference value. At 1 °C, inoculated Salmonella was reduced in 6.61 ln CFU.g-1 (2.87 log CFU.g-1). These results demonstrated the importance of establishing in legislation, especially in Brazil, standard values of deteriorating microorganisms in beef for maintaining product quality.Neste estudo, os parâmetros cinéticos de bactérias mesófilas, psicrotróficas e ácido lácticas foram estimados em carne bovina embalada a vácuo a 1 °C e 4 °C, a partir de curvas experimentais produzidas em amostras estocadas durante 21 e 60 dias, respectivamente. Em um experimento separado, a sobrevivência de Salmonella enterica O:4,5 multirresistente (MDR) a 1°C também foi caracterizada. A vida de prateleira da carne bovina embalada a vácuo, estocada a 4°C, foi estimada em 16.1 dias (95% CI: 14.8 – 17.3 dias), enquanto que a 1 °C o período foi maior que 21 dias, porque a contagem estimada de mesófilos ao final do experimento foi de 12.5 ln UFC.g-1 (95% CI: 11.8 – 13.3 ln UFC.g-1), o qual é mais baixo que o valor referência de shelf-life. A 1 °C, Salmonella inoculada reduziu em 6.61 ln UFC.g-1 (2.87 log UFC.g-1). Estes resultados demonstram a importância de estabelecimento em legislação, especialmente no Brasil, de valores padrões para contagem de microrganismos deteriorantes em carnes visando manter a qualidade do produto.The authors thank the Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES), Brazil, for supporting the first author with a scholarship from the International Sandwich Exchange Program (PDSE) approved at the Call 047/2017/Process: 88881.189927/2018- 01. We also thank the Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq), Brazil (Process: 310462 / 2018-5), and the Instituto Federal de Educação, Ciência e Tecnologia de Mato Grosso (IFMT) for their support. Our gratitude also to the “Ad hoc” evaluators who reviewed our work and contributed to its improvement.info:eu-repo/semantics/publishedVersio

CheckThat! at CLEF 2020: Enabling the Automatic Identification and Verification of Claims in Social Media

We describe the third edition of the CheckThat! Lab, which is part of the 2020 Cross-Language Evaluation Forum (CLEF). CheckThat! proposes four complementary tasks and a related task from previous lab editions, offered in English, Arabic, and Spanish. Task 1 asks to predict which tweets in a Twitter stream are worth fact-checking. Task 2 asks to determine whether a claim posted in a tweet can be verified using a set of previously fact-checked claims. Task 3 asks to retrieve text snippets from a given set of Web pages that would be useful for verifying a target tweet's claim. Task 4 asks to predict the veracity of a target tweet's claim using a set of Web pages and potentially useful snippets in them. Finally, the lab offers a fifth task that asks to predict the check-worthiness of the claims made in English political debates and speeches. CheckThat! features a full evaluation framework. The evaluation is carried out using mean average precision or precision at rank k for ranking tasks, and F1 for classification tasks.Comment: Computational journalism, Check-worthiness, Fact-checking, Veracity, CLEF-2020 CheckThat! La

Thread-level information for comment classification in community question answering

Community Question Answering (cQA) is a new application of QA in social contexts (e.g., fora). It presents new interesting challenges and research directions, e.g., exploiting the dependencies between the different comments of a thread to select the best answer for a given question. In this paper, we explored two ways of modeling such dependencies: (i) by designing specific features looking globally at the thread; and (ii) by applying structure prediction models. We trained and evaluated our models on data from SemEval-2015 Task 3 on Answer Selection in cQA. Our experiments show that: (i) the thread-level features consistently improve the performance for a variety of machine learning models, yielding state-of-the-art results; and (ii) sequential dependencies between the answer labels captured by structured prediction models are not enough to improve the results, indicating that more information is needed in the joint model

Contaminación por Staphylococcus aureus en el procesamiento de un embutido fermentado português (linguiça)

Linguiça is a Portuguese dry-fermented sausage, which has been found to harbour food-borne pathogens in the past. Hence, the objective of this study was to investigate the levels of total viable counts (TVC), Enterobacteriaceae, and S. aureus at the key production stages of linguiça by depicting their changes using principal component analysis. Unlike Enterobacteriaceae counts, which decreased from raw meat to final product, S. aureus increased significantly in the meats throughout processing. While Enterobacteriaceae was very sensitive to the decrease in water activity, S. aureus remained viable and developed during fermentation. The presence of S. aureus at all stages should prompt industries to reinforce good hygiene practices in the processing of linguiça.Esta investigación se realizó dentro del proyecto PTDC/AGR-TEC/3107/2012, financiado por la Fundación Portuguesa de Ciencia y Tecnología (FCT)/Fondos Europeos de Desarrollo Regional (FEDER). La Dra. Gonzales-Barron agradece el apoyo financiero provisto por la FCT a través del programa "Investigator Fellowship" (IF/00570)info:eu-repo/semantics/publishedVersio