In recent years several efforts were devoted to automatically mining opinions and sentiments from natural language in social media messages, news and commercial product reviews. Since this task involves a deep understanding of the explicit and implicit information conveyed by the language, most of the approaches refer to annotated corpora. However, the development of this kind of resource raises several new challenges due both to the specificity of the data from such domains and text genres, and to the knowledge to be annotated.This paper focusses on the main issues related to the development of a corpus for opinion and sentiment analysis, with a special attention to irony, and presents as a case study Senti-TUT, an ongoing project for Italian aimed at investigating sentiment and irony about politics in social media. We introduce and analyze the Senti-TUT corpus, a collection of texts from Twitter annotated morpho-syntactically and with sentiment polarity. We describe the dataset, the annotation, the methodologies applied and our investigations on two important features of irony: polarity reversing and emotion expressions.

Nutritional status is one of the most relevant prognostic factors in Amyotrophic Lateral Sclerosis (ALS), and close monitoring can help avoid severe weight loss over the disease course. We describe the impact of a Chatbot webapp on improving the communications between physicians, patients, and/or caregivers for dietary monitoring. We developed a chatbot that provides patients with a tool to register their meals through an intuitive and carefully designed conversational interface. Patients recorded their dietary intake twice weekly and received an adequate nutritional recommendation monthly. We monitored their functional and nutritional parameters. The data were compared with a control group followed up by standard counseling. We enrolled 26 patients. Regarding feasibility, 96% of participants completed the three-month follow-up, and 77% ended the six months. Regarding the change in weight in the Chatbot group, we observed a weight stabilization (F = 1.874, p-value: 0.310 for changes) over the telehealth compared to the control group (F = 1.710, p-value: 0.024 for changes). A telehealth approach for nutritional support is feasible and reproducible in an ALS setting: frequent monitoring turned out to help prevent further weight loss, allowing an early nutritional strategy adjustment.

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Abstract. This paper proposes a software architecture for automatic diet management and recipes analysis. We design a virtual dietitian that is able: (1) to recover the nutritional information directly from a specific recipe, (2) to reason over recipes and diets with flexibility, i.e. by allowing some forms of diet disobedience, and (3) to persuade the user to minimize these acts of disobedience.

Starting from the first edition held in 2007, EVALITA is the initiative for the evaluation of Natural Language Processing tools for Italian. This paper describes the EVALITA4ELG project, whose main aim is at systematically collecting the resources released as benchmarks for this evaluation campaign, and making them easily accessible through the European Language Grid platform. The collection is moreover integrated with systems and baselines as a pool of web services with a common interface, deployed on a dedicated hardware infrastructure.

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