Napredna analitika društvenih medija za predviđanje poslovne krize

master's thesis

• Title (english): Advanced social media analytics for business crisis prediction
• Author: Marija Skelin
• Mentor: Mirjana Pejić Bach (mentor)
• Committee member: Davor Labaš (član povjerenstva)
• Committee member: Andrija Sabol (član povjerenstva)
• Granter: University of Zagreb; Faculty of Economics and Business; (Department of Managerial Economics); Zagreb
• Defense date and country: 2023-11-07, Croatia
• Scientific / art field, discipline and subdiscipline: SOCIAL SCIENCES; Economics

Abstract

Predmet istraživanja u ovom radu je napredna analitika društvenih medija u predviđanju poslovne krize. Primarni cilj ovog diplomskog rada je prikazati prednosti upotrebe suvremene analitike društvenih medija za predviđanje poslovne krize. Sekundarni cilj odnosi se na prikaz funkcioniranja odabranog alata analize društvenih medija za predviđanje krize. Empirijski dio rada temelji se na istraživanju odabranog analitičkog alata društvenih medija kod predviđanja krize. Postoji mnogo dostupnih alata za područje analitike društvenih medija. Svaki od njih ima svoje primjene, prednosti i ograničenja. Također, svaki je prikladan za određene platforme društvenih medija. Za analizu je odobren Tweeterov (2023. promjena imena Tweeter u X) sustav za praćenje, analizu i razumijevanje tweetova koji se odnose na određenu temu. Za obradu podataka na Twitteru mogu se razmotriti dvije bitne tehnike, prva se zove pridruživanje pojmova, a druga se odnosi na analizu sentimenta što je ključno iz aspekta predviđanja poslovne krize. Za analizu podataka koristi se Twitter API, a kroz Twitterov proces analize velikih podataka tvrtke mogu dobiti vrijedne informacije o obrascima podataka i sentimentu teksta, što je ključno kod prediktivne analitike predviđanja poslovne krize upotrebom društvenih medija.

Abstract (english)

The subject of research in this paper is advanced analytics of social media in predicting business crises. The primary goal of this thesis is to show the advantages of using modern social media analytics to predict business crises. The secondary objective refers to the demonstration of the functioning of the selected social media analysis tool for crisis prediction. The empirical part of the paper is based on the research of the selected analytical tool of social media in crisis forecasting. There are many tools available in the field of social media analytics. Each of them has its own applications, advantages and limitations. Also, each is suitable for specific social media platforms. Tweeter's (in 2023, the name Tweeter changes to X) system for tracking, analyzing and understanding tweets related to a specific topic was approved for analysis. Two essential techniques can be considered for data processing on Twitter, the first is called term association, and the second is related to sentiment analysis, which is crucial from the aspect of predicting a business crisis. The Twitter API is used for data analysis, and through Twitter's big data analysis process, companies can gain valuable information about data patterns and text sentiment, which is key to predictive analytics for predicting business crises using social media.

• Keywords: analitički alati; društveni mediji; poslovna kriza; predviđanje
• Keywords (english): analytics tools; social media; business crisis; prediction
• Language: croatian
• URN:NBN: urn:nbn:hr:148:327026
• Study programme: Title: Business economics; Study programme type: university; Study level: integrated undergraduate and graduate; Academic / professional title: sveučilišni magistar ekonomije/sveučilišna magistra ekonomije (sveučilišni magistar ekonomije/sveučilišna magistra ekonomije)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Access restricted to students and staff of home institution
• Created on: 2023-11-08 13:09:53