The Networked Cultural Diffusion of KpopA webometric approach to examine actors, networks and

content in YouTube-based diffusion• Weiai (Wayne) Xu, PhD Candidate, Department of Communication, SUNY-Buffalo

• Ji Young Park, Interdisciplinary Program of East Asian Cultural Studies, YeungNam University

• Jiyoung Kim, Cyber Emotions Research Center, YeungNam University

• Dr. Han Woo Park, Department of Media and Communication, YeungNam University

The Global Diffusion of Kpop

Daegu

Lima, Peru

U.S.A

Iran

The Role of Web 2.0 in Kpop DiffusionParticipatory, networked, and decentralized

User profiles

Comments

Ties

An Integrated Webometric Model for Web 2.0-based Cultural

Diffusion

RQs

Question 1: What are the demographic and behavioral characteristics of the

actors in YouTube-based cultural diffusions?

Question 2: What are the characteristics of peer interactions and shared interest

among the actors in YouTube-based cultural diffusions?

Question 3: What opinions are expressed by the actors in their evaluation of a

cultural offering on YouTube?

Methods

Profile analysis: gender, age and cultural identity (using location as a proxy

measure)

Network analysis: mutual-subscription networks (MSNs) and commentary

networks (CN)

Content analysis: Sentiment (using SentiStrength) and semantics

Data collection

• We used the API-based analysis program Webometric Analyst 2.0

to download 1,000 comments posted to Psy’s Gangnam style

video in August 2012 (a month after the initial release of the video)

• The sample has 983 valid comments contributed by 534 users

• 93,884 total comments at the time of data-collection

Findings - Actors

• 69% commenters are males

• The average age: 23.5

• U.S. (47%), UK (7%), Canada (7%), Korea (4%), Netherlands

(3%)…

Findings - Network

Commentary networks

Mutual-subscription networks

Findings - Network

Actors by top centrality

User IDsIncoming

replies

Outgoing

replies

Incoming

repliers

Outgoing

repliersAge Gender Location

Argo*** 86 42 28 15 35 M US

Julius Vil*** 42 12 18 6 N.A. N.A. N.A.

jackie chan*** 30 4 14 2 N.A. N.A. N.A.

Neuron*** 22 4 9 2 N.A. M US

**** 20 24 10 9 N.A. N.A. N.A.

TheSocklessMon*** 18 14 6 5 N.A. M US

DarealRadexHE*** 16 6 4 2 28 M PL

Hinata*** 16 2 8 1 14 F ES

Gamink*** 16 6 8 3 N.A. M CA

Findings - Network

Network variations along user characteristics

• Based on peer interactions (CN), male commenters were more likely to have continuous discussions than female commenters.

• Commenters in their twenties were most likely to participate in peer interactions (i.e. replying to comments), followed by those in their teens and younger, thirties, and forties and older.

• Based on mutual interest (MSN), there was a greater overlap in topical interests for male commenters than for female commenters.

• The overlap in topic interests was most prominent among those in their twenties and teens and younger.

Findings - Network

Most subscribed YouTube channels by the commenters

# of subscribers Channels Characteristics5460 NIGAH*** reaction videos on various topics

3486 FREDD*** active and peculiar videos

3321 SM*** To gag and be critical

2775 RAYWILLIAMJOHN*** Comic books and hip-hop music

2346 BIGB*** Official BIGBANG YouTube channel

2016 2NE1 Official 2NE1 YouTube channel

1711 EPICMEALT*** Criticisms about high-calorie foods

1711 KEVJU***Being sociable and uploading videos about jokes and school problems

1596 SMTOWN Official SMTOWN YouTube channel

1378 FPSRUS*** Guns and explosives

1225 MACHIN***The premier global video entertainment network for gamers featuring gameplay videos, trailers, original series, and live streams, among others

1225 YGENTERTAINMENT Official YG Entertainment YouTube channel

Findings - Content

Semantic network

There was a frequent mention of cultural and geographic terms such as Korea (392) and Japan (465). Korean figures and organizations were among those terms most frequently mentioned, including Hyuna (a Kpop artist appearing in the GS video) and YG (a Psy-affiliated firm)

Findings - Content

Sentiment

• Sentiment strength was measured on a scale from -5 to 5, with 5 indicating extremely positive attitudes, whereas -5, extremely negative sentiments.

• Comments with moderately favorable views (+3 and +2) outnumbered those with moderately unfavorable ones (-3 and -2) by about 100.

Sentiment 1 2 3 4 5

Positive 566 252 138 10 1

Negative 626 151 114 67 9

Note: N=967.

Findings - Content

Sentiment variations by user characteristics

• The more culturally distant from Korea in terms of power distance, the less likely the positive sentiment toward the GS.

• The more dissimilar the country to Korea in terms of both individualism and masculinity, the more likely the negative comment.

Insights in Summary

• The actors in the diffusion of the GS video were young YouTube users living in North America and Europe.

• Interactions flowed between a small set of users, and most users represented a silent majority who only subscribed to the video channel but did not interact with other users.

• Commenters were interested in the cultural origin of the video and related media content to the broader national and cultural image of a foreign country

• Users whose cultural background is similar to Korean culture are more likely to favor GS video.

The Big Picture

• The theoretical contribution: connecting a webometric approach to the study of innovators and early adopters in the evaluation stage of cultural diffusion.

• The methodological contribution: integrating multiple webometric approaches (social network analysis, semantic analysis and sentiment analysis) to address three elements in diffusion (actors, relationship and content)

THANK YOU!

Weiai (Wayne) Xu, weiaixu@buffalo.edu

http://curiositybits.com/