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    Wyświetlanie 1-5 z 5
    Tytuł:
    Cultura francese e cultura polacca in Giuseppe Mazzini
    French Culture and Polish Culture in Giuseppe Mazzini
    Kultura Francuska I Kultura Polska U Giuseppe Mazziniego
    Autorzy:
    Fournier-Finocchiaro, Laura
    Powiązania:
    https://bibliotekanauki.pl/articles/2076615.pdf
    Data publikacji:
    2016
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    Giuseppe Mazzini
    French literature
    Polish Romanticism
    Anti-French sentiment
    Italy-Poland relations
    Opis:
    During the 19th century, Giuseppe Mazzini communicated to his contemporaries the feeling of a strong hostility against France, to defend his project of emancipation of Italy (and Europe) from French tutelage. So he decided to choose other models and other examples, in European literature, that could serve as a guide and reference point. In particular, he was influenced by Polish poets, who convinced him that poetry could animate the “Europe of the people” and guide them to achieve the major objectives of the “new epoch”. Polish literature is the origin of Mazzini’s exaltation of Risorgimento poetry and constituted a positive reference point to counter the decline and loss of influence of French culture.
    Źródło:
    Kwartalnik Neofilologiczny; 2016, 2; 176-186
    0023-5911
    Pojawia się w:
    Kwartalnik Neofilologiczny
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Parlamentarne ćwierkanie o pandemii. Analiza sentymentu tweetów parlamentarzystów publikowanych podczas pierwszych 12 miesięcy pandemii koronawirusa w Polsce
    Parliamentary Tweeting About the Pandemic. The Sentiment of Parliamentarians’ Tweets Published During the First 12 Months of the Coronavirus Pandemic in Poland Analysed
    Autorzy:
    Meler, Andrzej
    Powiązania:
    https://bibliotekanauki.pl/articles/2131898.pdf
    Data publikacji:
    2022
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    komunikacja polityczna
    Twitter
    analiza sentymentu
    populizm
    COVID-19
    political communication
    sentiment analysis
    populism
    Opis:
    W czasie pandemii koronawirusa istotnym zagadnieniem stało się zarządzanie kryzysem, a w nim – zarządzanie społecznymi emocjami. Przedstawiona w artykule analiza sentymentu oparta na słowniku NAWL dotyczy postów polskich parlamentarzystów zamieszczanych na Twitterze podczas pierwszych 12 miesięcy pandemii. Pozwala ona określić w sposób ilościowy zakres uwagi poświęcony pandemii w tym medium społecznościowym w relacji do innych tematów. Umożliwia także zidentyfikowanie istotnych różnic pomiędzy sentymentem postów publikowanych przez parlamentarzystów obozu rządzącego i opozycji, postów na temat pandemii i na inne tematy.
    During the coronavirus pandemic, crisis management, including the management of social emotions, became an important issue. The sentiment analysis based on the NAWL dictionary presented in the article concerns the posts of Polish parliamentarians posted on Twitter during the first 12 months of the pandemic. It allows to quantify the scope of attention devoted to the pandemic in this social medium in relation to other topics. It also makes it possible to identify significant differences between the sentiment of posts published by parliamentarians in the government camp and the opposition as well as between the posts on the pandemic and on other topics.
    Źródło:
    Studia Socjologiczne; 2022, 2; 113-136
    0039-3371
    Pojawia się w:
    Studia Socjologiczne
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Exploring the use of syntactic dependency features for document-level sentiment classification
    Autorzy:
    Kalaivani, K. S.
    Kuppuswami, S.
    Powiązania:
    https://bibliotekanauki.pl/articles/201609.pdf
    Data publikacji:
    2019
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    document-level sentiment classification
    syntactic dependency features
    generalized dependency features
    information gain
    weighted frequency
    weighted odds
    zdobywanie informacji
    częstotliwość
    szanse
    Opis:
    An automatic analysis of product reviews requires deep understanding of the natural language text by machine. The limitation of bag-of-words (BoW) model is that a large amount of word relation information from the original sentence is lost and the word order is ignored. Higher-order-N-grams also fail to capture the long-range dependency relations and word order information. To address these issues, syntactic features extracted from the dependency relations can be used for machine learning based document-level sentiment classification. Generalization of syntactic dependency features and negation handling is used to achieve more accurate classification. Further to reduce the huge dimensionality of the feature space, feature selection methods based on information gain (IG) and weighted frequency and odds (WFO) are used. A supervised feature weighting scheme called delta term frequency-inverse document frequency (TF-IDF) is also employed to boost the importance of discriminative features using the observed uneven distribution of features between the two classes. Experimental results show the effectiveness of generalized syntactic dependency features over standard features for sentiment classification using Boolean multinomial naive Bayes (BMNB) classifier.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2019, 67, 2; 339-347
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Aspect-based sentiment classification model employing whale-optimized adaptive neural network
    Autorzy:
    Balaganesh, Nallathambi
    Muneeswaran, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/2173622.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    aspect-based sentiment analysis
    whale optimization algorithm
    artificial neural network
    opinion mining
    analiza nastrojów oparta na aspektach
    algorytm optymalizacji wielorybów
    sztuczna sieć neuronowa
    eksploracja opinii
    Opis:
    Nowadays in e-commerce applications, aspect-based sentiment analysis has become vital, and every consumer started focusing on various aspects of the product before making the purchasing decision on online portals like Amazon, Walmart, Alibaba, etc. Hence, the enhancement of sentiment classification considering every aspect of products and services is in the limelight. In this proposed research, an aspect-based sentiment classification model has been developed employing sentiment whale-optimized adaptive neural network (SWOANN) for classifying the sentiment for key aspects of products and services. The accuracy of sentiment classification of the product and services has been improved by the optimal selection of weights of neurons in the proposed model. The promising results are obtained by analyzing the mobile phone review dataset when compared with other existing sentiment classification approaches such as support vector machine (SVM) and artificial neural network (ANN). The proposed work uses key features such as the positive opinion score, negative opinion score, and term frequency-inverse document frequency (TF-IDF) for representing each aspect of products and services, which further improves the overall effectiveness of the classifier. The proposed model can be compatible with any sentiment classification problem of products and services.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; art. no. e137271
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Aspect-based sentiment classification model employing whale-optimized adaptive neural network
    Autorzy:
    Balaganesh, Nallathambi
    Muneeswaran, K.
    Powiązania:
    https://bibliotekanauki.pl/articles/2128172.pdf
    Data publikacji:
    2021
    Wydawca:
    Polska Akademia Nauk. Czytelnia Czasopism PAN
    Tematy:
    aspect-based sentiment analysis
    whale optimization algorithm
    artificial neural network
    opinion mining
    analiza nastrojów oparta na aspektach
    algorytm optymalizacji wielorybów
    sztuczna sieć neuronowa
    eksploracja opinii
    Opis:
    Nowadays in e-commerce applications, aspect-based sentiment analysis has become vital, and every consumer started focusing on various aspects of the product before making the purchasing decision on online portals like Amazon, Walmart, Alibaba, etc. Hence, the enhancement of sentiment classification considering every aspect of products and services is in the limelight. In this proposed research, an aspect-based sentiment classification model has been developed employing sentiment whale-optimized adaptive neural network (SWOANN) for classifying the sentiment for key aspects of products and services. The accuracy of sentiment classification of the product and services has been improved by the optimal selection of weights of neurons in the proposed model. The promising results are obtained by analyzing the mobile phone review dataset when compared with other existing sentiment classification approaches such as support vector machine (SVM) and artificial neural network (ANN). The proposed work uses key features such as the positive opinion score, negative opinion score, and term frequency-inverse document frequency (TF-IDF) for representing each aspect of products and services, which further improves the overall effectiveness of the classifier. The proposed model can be compatible with any sentiment classification problem of products and services.
    Źródło:
    Bulletin of the Polish Academy of Sciences. Technical Sciences; 2021, 69, 3; e137271, 1--8
    0239-7528
    Pojawia się w:
    Bulletin of the Polish Academy of Sciences. Technical Sciences
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-5 z 5

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