Determining the Veracity of Rumours on Twitter

While social networks can provide an ideal platform for up-to-date information from individuals across the world, it has also proved to be a place where rumours fester and accidental or deliberate mis- information often emerges. In this article, we aim to support the task of making sense from social media data, and specifically, seek to build an autonomous message-classifier that filters relevant and trustworthy information from Twitter. For our work, we collected about 100 million public tweets, including users’ past tweets, from which we identified 72 rumours (41 true, 31 false). We considered over 80 trustworthiness measures including the authors’ profile and past behaviour, the social network connections (graphs), and the content of tweets themselves. We ran modern machine-learning classifiers over those measures to produce trustworthiness scores at various time windows from the outbreak of the rumour. Such time-windows were key as they allowed useful insight into the progression of the rumours. From our findings, we identified that our model was significantly more accurate than similar studies in the literature. We also identified critical attributes of the data that give rise to the trustworthiness scores assigned. Finally we developed a software demonstration that provides a visual user interface to allow the user to examine the analysis

Changing trends in mastitis

<p>Abstract</p> <p>The global dairy industry, the predominant pathogens causing mastitis, our understanding of mastitis pathogens and the host response to intramammary infection are changing rapidly. This paper aims to discuss changes in each of these aspects. Globalisation, energy demands, human population growth and climate change all affect the dairy industry. In many western countries, control programs for contagious mastitis have been in place for decades, resulting in a decrease in occurrence of <it>Streptococcus agalactiae </it>and <it>Staphylococcus aureus </it>mastitis and an increase in the relative impact of <it>Streptococcus uberis </it>and <it>Escherichia coli </it>mastitis. In some countries, <it>Klebsiella </it>spp. or <it>Streptococcus dysgalactiae </it>are appearing as important causes of mastitis. Differences between countries in legislation, veterinary and laboratory services and farmers' management practices affect the distribution and impact of mastitis pathogens. For pathogens that have traditionally been categorised as contagious, strain adaptation to human and bovine hosts has been recognised. For pathogens that are often categorised as environmental, strains causing transient and chronic infections are distinguished. The genetic basis underlying host adaptation and mechanisms of infection is being unravelled. Genomic information on pathogens and their hosts and improved knowledge of the host's innate and acquired immune responses to intramammary infections provide opportunities to expand our understanding of bovine mastitis. These developments will undoubtedly contribute to novel approaches to mastitis diagnostics and control.</p