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Napovedovanje gibanja vrednosti delniškega indeksa Dow Jones s pomočjo zapisov na družbenih omrežjih
ID MATJAŠIČ, SABINA (Author), ID Hovelja, Tomaž (Mentor) More about this mentor... This link opens in a new window

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Abstract
Družabna omrežja imajo čedalje večje število uporabnikov. Iz tega razloga smo se odločili preučiti, ali lahko z analizo mnenj, ki jih objavljajo uporabniki, napovemo nihanje trga. Zgradili smo napovedni model in preučili, ali najdemo povezavo med nihanjem vrednosti delnic in nihanjem sentimenta na družabnem omrežju. Za analizo smo si izbrali enega najbolj prepoznavnih delniških indeksov na svetu Dow Jones, ki vsebuje 30 zelo velikih podjetij. V sentimentalno analizo smo vključili tvite ljudi, ki so na vodilnih položajih v posameznih podjetjih, ki so vsebovana v indeksu. Na ta način smo dobili splošno razpoloženje med vodilnimi vsakega podjetja in dokazali medsebojno povezanost med sentimentom na družabnih omrežjih in nihanjem trga.

Language:Slovenian
Keywords:Twitter, analiza, napovedovanje
Work type:Bachelor thesis/paper
Typology:2.11 - Undergraduate Thesis
Organization:FRI - Faculty of Computer and Information Science
Year:2020
PID:20.500.12556/RUL-120046 This link opens in a new window
COBISS.SI-ID:31187459 This link opens in a new window
Publication date in RUL:15.09.2020
Views:2239
Downloads:893
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Secondary language

Language:English
Title:Forecasting the movement of the value of stocks with the help of records from social network
Abstract:
Social networks have an increasing number of users. For this reason, we decided to examine whether market fluctuations can be predicted by analyzing the opinions posted by them. We built a predictive model and examined whether we found a link between fluctuations in stock values and fluctuations in sentiment on the social network. For the analysis, we chose one of the most recognizable stock indexes in the world, the Dow Jones index, which contains 30 very large companies. In the sentimental analysis, we included tweets of people who are in leading positions in individual companies contained in the Dow Jones index. In this way, we got a general mood among the leaders of each company and proved the connection between sentiment on social networks and market fluctuations.

Keywords:Twitter, analysis, forecasting

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