Analiza sentimenta u komunikaciji na Twitchu

undergraduate thesis

• Title (english): Sentiment Analysis of Twitch Chats
• Author: Leonardo Čuljak
• Mentor: Marina Bagić Babac (mentor)
• Committee member: Marina Bagić Babac (predsjednik povjerenstva)
• Committee member: Mirjana Domazet-Lošo (član povjerenstva)
• Committee member: Krešimir Fertalj (član povjerenstva)
• Granter: University of Zagreb; Faculty of Electrical Engineering and Computing; Zagreb
• Defense date and country: 2020-07-15, Croatia
• Scientific / art field, discipline and subdiscipline: TECHNICAL SCIENCES; Computing

Abstract

Video igre su tradicionalno uvijek bile društvene, gdje arkade pružaju mogućnost javne igre, a konzole mogućnost zajedničkog igranja kod kuće. Gledatelji nisu ograničeni na pasivno gledanje jer mogu izravno uživo komunicirati s igračem. Danas Twitch.tv dominira u gotovo svim zemljama u prijenosu video igara uživo. U takvim igrama dominiraju, tzv. streameri - visoko kvalificirani igrači koji minimalno komuniciraju pa je cilj ovog završnog rada proučiti zajedničke komunikacijske karakteristike gledatelja koji često šalju pojedinačne poruke i streamera koji ih razrađuju. Na temelju velikog stvarnog skupa podataka chatova uživo, ovaj rad pomoću analize sentimenta istražuje i uspoređuje nalaze različitih teorija komunikacije o gledateljima i kako oni doživljavaju streamere duž spektra različitih sentimenata.

Abstract (english)

Video gameplay has traditionally been social, with arcades providing an outlet for public play and consoles, allowing people to play together at home. Onlookers are not limited to being passive spectatorships as they are also provided the opportunity to engage directly with the player, with gameplay livestreaming being the newest iteration. Live streaming of video games has become dominated in most countries by the website Twitch.tv, where challenge concerns highly skilled players with minimal communication and exchange, conversely, prioritizes showmanship over gameplay. This thesis focuses on common communication characteristics of viewers who often send single messages and streamers who elaborate. Based on a large real dataset of livestream chats, this thesis uses sentiment analysis to explore and compare the findings of different communication theories regarding viewers and how they perceive streamers along the spectrum of different sentiments.

• Keywords: Twitch.TV; analiza osjećaja; Obrada prirodnog jezika
• Keywords (english): Twitch.TV; sentiment analysis; VADER; Natural Language Processing
• Language: english
• URN:NBN: urn:nbn:hr:168:006063
• Study programme: Title: Computing; Study programme type: university; Study level: undergraduate; Academic / professional title: sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva (sveučilišni/a prvostupnik/ prvostupnica (baccalaureus/baccalaurea) inženjer/inženjerka računarstva)
• Type of resource: Text
• File origin: Born digital
• Access conditions: Closed access
• Created on: 2023-01-14 08:40:06