MARC보기
LDR00000nam u2200205 4500
001000000435897
00520200228110505
008200131s2019 ||||||||||||||||| ||eng d
020 ▼a 9781392787915
035 ▼a (MiAaPQ)AAI27667168
040 ▼a MiAaPQ ▼c MiAaPQ ▼d 247004
0820 ▼a 300
1001 ▼a Leith, Alex P.
24510 ▼a Gameplay Livestreaming: Human Agents of Gamespace and Their Parasocial Relationships.
260 ▼a [S.l.]: ▼b Michigan State University., ▼c 2019.
260 1 ▼a Ann Arbor: ▼b ProQuest Dissertations & Theses, ▼c 2019.
300 ▼a 101 p.
500 ▼a Source: Dissertations Abstracts International, Volume: 81-06, Section: B.
500 ▼a Advisor: Ratan, Rabindra.
5021 ▼a Thesis (Ph.D.)--Michigan State University, 2019.
506 ▼a This item must not be sold to any third party vendors.
520 ▼a Gameplay livestreaming is an increasingly popular form of media with tens of thousands of people choosing to do it as either a hobby or career. Once each of these individuals creates a Twitch account and starts broadcasting themselves, they become a media figure. This dissertation examined the chats from thousands of partnered Twitch channels. The two key areas of examination are parasocial relationships and gameplay engagement. Parasocial relationshxips state that media users can begin to develop perceived relationships with media figures as they consume content containing that figure. A series of Python bots gathered chat and stream data over a month from 30 Twitch categories (e.g., Hearthstone, League of Legends, Art, and Just Chatting). The bots logged a total of 321,189,309 messages from 6,564,307 senders and 117,943 channels. After cleaning the data for partnership status, stream language, and message count, coding divided the remaining 3,224,942 messages from 1,298,148 senders and 3,127 channels into their appropriate groups (i.e., messages target and stream content). The research hypotheses subdivided the dataset several times. All hypotheses had the messages separated between streamer-specific messages and other-specific messages. Streamer-specific messages are messages which include the at symbol ( ) and the channel name, thus signaling message intentionality to the streamer. Hypotheses two further divided the messages between gameplay and non-gameplay streams, and hypothesis three divided the messages from gameplay streams into entertainment and expertise streams. The hypotheses persistently found that the message target was a reliable predictor of verbal immediacy, the metric used to identify parasocial relationships. Stream content either proved to be a counter-intuitive predictor or no predictor of verbal immediacy. Grounded theory methods addressed the research questions and produced two common distinctions for gameplay involvement. Viewers can engage with gameplay by asking questions but can also elevate themselves to human agents of gamespace through providing information or suggestions.
590 ▼a School code: 0128.
650 4 ▼a Communication.
650 4 ▼a Psychology.
650 4 ▼a Mass communications.
690 ▼a 0708
690 ▼a 0459
690 ▼a 0621
71020 ▼a Michigan State University. ▼b Information and Media - Doctor of Philosophy.
7730 ▼t Dissertations Abstracts International ▼g 81-06B.
773 ▼t Dissertation Abstract International
790 ▼a 0128
791 ▼a Ph.D.
792 ▼a 2019
793 ▼a English
85640 ▼u http://www.riss.kr/pdu/ddodLink.do?id=T15494642 ▼n KERIS ▼z 이 자료의 원문은 한국교육학술정보원에서 제공합니다.
980 ▼a 202002 ▼f 2020
990 ▼a ***1008102
991 ▼a E-BOOK