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undergraduate thesis
Korištenje Pythona u analizi sentimenta
Zagreb: University of Zagreb, Faculty of Humanities and Social Sciences, 2022. urn:nbn:hr:131:524660
Tokić, Anamaria
University of Zagreb
Faculty of Humanities and Social Sciences
Department of information and Communication sciences

Institutional repository: ODRAZ

Cite this document

Tokić, A. (2022). Korištenje Pythona u analizi sentimenta (Undergraduate thesis). Zagreb: University of Zagreb, Faculty of Humanities and Social Sciences. Retrieved from https://urn.nsk.hr/urn:nbn:hr:131:524660

Tokić, Anamaria. "Korištenje Pythona u analizi sentimenta." Undergraduate thesis, University of Zagreb, Faculty of Humanities and Social Sciences, 2022. https://urn.nsk.hr/urn:nbn:hr:131:524660

Tokić, Anamaria. "Korištenje Pythona u analizi sentimenta." Undergraduate thesis, University of Zagreb, Faculty of Humanities and Social Sciences, 2022. https://urn.nsk.hr/urn:nbn:hr:131:524660

Tokić, A. (2022). 'Korištenje Pythona u analizi sentimenta', Undergraduate thesis, University of Zagreb, Faculty of Humanities and Social Sciences, accessed 24 November 2024, https://urn.nsk.hr/urn:nbn:hr:131:524660

Tokić A. Korištenje Pythona u analizi sentimenta [Undergraduate thesis]. Zagreb: University of Zagreb, Faculty of Humanities and Social Sciences; 2022 [cited 2024 November 24] Available at: https://urn.nsk.hr/urn:nbn:hr:131:524660

A. Tokić, "Korištenje Pythona u analizi sentimenta", Undergraduate thesis, University of Zagreb, Faculty of Humanities and Social Sciences, Zagreb, 2022. Available at: https://urn.nsk.hr/urn:nbn:hr:131:524660

Metadata
TitleKorištenje Pythona u analizi sentimenta
Title (english)Using Python for sentiment analysis
AuthorAnamaria Tokić
MentorTomislava Lauc (mentor)
Committee memberTomislava Lauc (član povjerenstva)
Committee memberVjera Lopina (član povjerenstva)
Committee memberSanja Kišiček (predsjednik povjerenstva)
GranterUniversity of Zagreb
Faculty of Humanities and Social Sciences
(Department of information and Communication sciences)
Zagreb
Defense date and country2022-09-05, Croatia
Scientific / art field,
discipline and subdiscipline		SOCIAL SCIENCES
Information and Communication Sciences
Abstract
Mišljenja, naša vlastita, ali i ona drugih ljudi, uvelike utječu na naše ponašanje i donošenje odluka. Želimo li, na primjer, kupiti novi proizvod prvo ćemo posegnuti za osvrtima, tj. mišljenjima drugih ljudi o njemu. Analiza sentimenta ili dubinsko pretraživanje mišljenja se odnosi na računalnu obradu prirodnog jezika kojom se analiziraju stavovi i mišljenja pojedinaca o nekom proizvodu, temi, usluzi i slično. Ovaj će se završni rad baviti primjenom programskog jezika Python u analizi sentimenta. Posebno će se koristiti biblioteke Pandas, NLTK i Scikit-learn te njihove metode i funkcije. Također, bit će prikazani klasifikatori, s posebnim osvrtom na Naivni Bayesov klasifikator te logističku regresiju. Korpus koji će biti korišten u primjerima je korpus osvrta s Amazona koji je preuzet s poveznice: https://www.coursera.org/learn/python-text-mining/resources/d9pwm
Abstract (english)
Opinions, our own and those of other people, influence our behavior and decision-making. If, for example, we want to buy a new product, we will first look for reviews, i.e. other people's opinion about it. Sentiment analysis or opinion mining refers to computer processing of natural language, which analyzes the attitudes and opinions of individuals about e.g. a product, topic or a service. This paper will deal with the application of the Python programming language in sentiment analysis. In particular with Pandas, NLTK and Scikit-learn libraries and their methods and function. Also, classifiers will be presented, with a special focus on the Naive Bayes classifier and logistic regression. The corpus that will be used in the examples is the review corpus from Amazon downloaded from the links: https://www.coursera.org/learn/python-text-mining/resources/d9pwm
Keywords
Keywords (english)
Languagecroatian
URN:NBNurn:nbn:hr:131:524660
Study programmeTitle: Information Sciences
Study programme type: university
Study level: undergraduate
Academic / professional title: sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) informacijskih znanosti (sveučilišni/a prvostupnik/prvostupnica (baccalaureus/baccalaurea) informacijskih znanosti)
Type of resourceText
File originBorn digital
Access conditionsOpen access
Terms of useLicence In copyright icon
Created on2022-09-15 09:01:14