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    Wyświetlanie 1-4 z 4
    Tytuł:
    Sentiment Analysis of German Texts in Finance: Improving and Testing the BPW Dictionary
    Autorzy:
    Pöferlein, Matthias
    Powiązania:
    https://bibliotekanauki.pl/articles/2048284.pdf
    Data publikacji:
    2021-12-20
    Wydawca:
    Uniwersytet Warszawski. Wydawnictwo Naukowe Wydziału Zarządzania
    Tematy:
    textual analysis
    textual sentiment
    sentiment analysis
    content analysis
    CEO speeches
    annual general meeting
    Opis:
    Using the dictionary-based approach to measure the sentiment of finance-related texts is primarily focused on English-speaking content. This is due to the need for domain-specific dictionaries and the primary availability of those in English. Through the contribution of Bannier et al. (2019b), the first finance-related dictionary is available for the German language. Because of the novelty of this dictionary, this paper proposes several reforms and extensions of the original word lists. Additionally, I tested multiple measurements of sentiment. I show that using the edited and extended dictionary to calculate a relative measurement of sentiment, central assumptions regarding textual analysis can be fulfilled and more significant relations between the sentiment of a speech by a CEO at the Annual General Meeting and subsequent abnormal stock returns can be calculated.
    Źródło:
    Journal of Banking and Financial Economics; 2021, 2(16); 5-24
    2353-6845
    Pojawia się w:
    Journal of Banking and Financial Economics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Exploring the Impact of Negative Words Used in Online Feedback in Hotel Industry: A Sentiment Analysis, N-gram, and Text Network Analysis Approach
    Autorzy:
    Dan, Daniel
    Powiązania:
    https://bibliotekanauki.pl/articles/32307710.pdf
    Data publikacji:
    2023-03-22
    Wydawca:
    Uniwersytet Warszawski. Wydawnictwo Naukowe Wydziału Zarządzania
    Tematy:
    sentiment analysis
    tourism
    hotels
    marketing
    customer’s opinions
    Opis:
    This study examines the words and situations that trigger and those that do not trigger a hotel response when customers post negative online feedback. The research explores, through sentiment analysis, bigrams, trigrams, and word networking, the valence of online reviews of five important hotels in Las Vegas. Only the feedback that has been categorized as negative by the algorithm is selected. In correspondence to this feedback, the existence of answers from the hotels is checked together with the response style. While the negative valence of the feedback can represent a mixture of subjective and objective emotions, there are common features present in their expression. On the responses side from the hotel, not all the reviews receive attention. As such, the negative feedback words are extracted and separated into those that belong to reviews that obtain a response and those that do not. The replies are standardised by following an established pattern. This paper aims to contribute to a prominent issue in tourism that is little tackled: responses to feedback. The findings may help the hotels’ management explore different paths to improve their services and responses alike. Behavioural marketing researchers might want to use these results to confirm the existence of such patterns in different datasets or situations.
    Źródło:
    Journal of Marketing and Consumer Behaviour in Emerging Markets; 2023, 1(16); 39-50
    2449-6634
    Pojawia się w:
    Journal of Marketing and Consumer Behaviour in Emerging Markets
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    Gender and socio-economic differences in South African consumers’ sentiments toward marketing practices
    Autorzy:
    Roux, Thérèse
    Powiązania:
    https://bibliotekanauki.pl/articles/41189025.pdf
    Data publikacji:
    2023-06-07
    Wydawca:
    Uniwersytet Warszawski. Wydawnictwo Naukowe Wydziału Zarządzania
    Tematy:
    consumer attitudes
    demographics
    marketing practices
    consumers’ sentiment toward
    marketing
    CSM
    Opis:
    Studies on modern consumers’ sentiments toward marketing in an emerging market context are vital. This paper compares demographic differences in South African consumers’ sentiment toward marketing. Data were collected via a survey with 444 diverse consumers residing in the Tshwane metropolitan area. The findings revealed that South African males are significantly less satisfied with marketing communication practices compared to females. Consumers earning lower income were signifi cantly less positive towards marketing in general as well as product quality, price, and selling practices. Afrikaans-speaking consumers’ attitudes were less positive towards marketing communication. The finding can guide the marketing industry to advance its image by adjusting its practices and coordinating with the government and other stakeholders to collaborate.
    Źródło:
    Journal of Marketing and Consumer Behaviour in Emerging Markets; 2023, 2(17); 1-16
    2449-6634
    Pojawia się w:
    Journal of Marketing and Consumer Behaviour in Emerging Markets
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
    Tytuł:
    The Impact of Investor Sentiment on Direction of Stock Price Changes: Evidence from the Polish Stock Market
    Autorzy:
    Polak, Kamil
    Powiązania:
    https://bibliotekanauki.pl/articles/2053925.pdf
    Data publikacji:
    2021-12-20
    Wydawca:
    Uniwersytet Warszawski. Wydawnictwo Naukowe Wydziału Zarządzania
    Tematy:
    sentiment analysis
    natural language processing
    machine learning
    financial forecasting
    behavioral finance
    Opis:
    The purpose of this research is to examine the impact of sentiment derived from news headlines on the direction of stock price changes. The study examines stocks listed on the WIG-banking sub-sector index on the Warsaw Stock Exchange. Two types of data were used: textual and market data. The research period covers the years 2015–2018. Through the research, 7,074 observations were investigated, of which 3,390 with positive sentiment, 2,665 neutral, and 1,019 negative. In order to examine the predictive power of sentiment, six machine learning models were used: Decision Tree Classifier, Random Forest Classifier, XGBoost Classifier, KNN Classifier, SVC and Gaussian Naive Bayes Classifier. Empirical results show that the sentiment of news headlines has no significant explanatory power for the direction of stock price changes in one-day time frame.
    Źródło:
    Journal of Banking and Financial Economics; 2021, 2(16); 72-90
    2353-6845
    Pojawia się w:
    Journal of Banking and Financial Economics
    Dostawca treści:
    Biblioteka Nauki
    Artykuł
      Wyświetlanie 1-4 z 4

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