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Si l'on connaît le penseur de la déréalisation du monde, de la déshumanisation du quotidien, de la marchandisation générale, les lecteurs français n'ont pas eu encore accès aux écrits plus personnels rédigés par le philosophe autrichien en exil. Les textes qui composent ce volume, extraits de ses journaux intimes de New York des années 1947-1949, ont pour objet des sentiments, les siens et ceux de ses compagnons de destin. Anders pour autant ne se livre pas en ces pages à l'exploration de sa vie intérieure, ni ne découvre des strates de son moi par goût de la confession. Les réactions émotionnelles qu'il consigne sont pour lui des exemples caractéristiques, appréhendés dans une perspective historique. Anders a fait valoir, dans le premier volume de L'Obsolescence de l'homme, l'intérêt d'une histoire du sentiment ; les pages qui suivent portent l'esquisse d'un tel projet, et l'amour en constitue le fil rouge. En 1979, Anders déclarait dans un entretien avec Mathias Greffrath : " [...] j'ai tenu un journal sur le fait amoureux en Amérique. Au moment où je l'ai écrit, il s'appelait Lieben heute (Aimer aujourd'hui). Maintenant, je l'ai rebaptisé Lieben gestern (Aimer hier). Et s'il paraît un jour, il faudra sans doute qu'il s'appelle Lieben vorgestren (Aimer avant-hier)... "

Sentiment --- Histoire

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Sentiment --- Emotie

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The importance of the Word of Mouth is growing day by day in many topics. This phenomenon is evident in everyday life, e.g., the rise of influencers and social media managers. If more people positively debate specific products, then even more people are encouraged to buy them and vice versa. This effect is directly affected by the relationship between the potential customer and the reviewer. Moreover, considering the negative reporting bias is evident in how the Word of Mouth analysis is of absolute interest in many fields. We propose an algorithm to extract the sentiment from a natural language text corpus. The combined approach of Neural Networks, with high predictive power but more challenging interpretation, with more simple but informative models, allows us to quantify a sentiment with a numeric value and to predict if a sentence has a positive (negative) sentiment. The assessment of an objective quantity improves the interpretation of the results in many fields. For example, it is possible to identify crucial specific sectors that require intervention, improving the company's services whilst finding the strengths of the company himself (useful for advertising campaigns). Moreover, considering that the time information is usually available in textual data with a web origin, to analyze trends on macro/micro topics. After showing how to properly reduce the dimensionality of the textual data with a data-cleaning phase, we show how to combine: WordEmbedding, K-Means clustering, SentiWordNet, and the Threshold-based Naïve Bayes classifier. We apply this method to Booking.com and TripAdvisor.com data, analyzing the sentiment of people who discuss a particular issue, providing an example of customer satisfaction.

Sentiment analysis.

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This contribution presents a methodological path tailored to highlight and manage the generating processes of Community-based cooperatives in Italian inner areas. Some quantitative techniques are involved, in particular multivariate statistical techniques, together with text analysis, in order to process the outcomes of a direct survey based on open responses. Moreover, a study of scenario, based on balance sheet data, is proposed, to verify the potential profitability of a new cooperative.

Sentiment analysis.

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Sentiment et conscience --- Conscience et sentiment