Comparing film and video game reviews:
-
Upload
tatyana-valdez -
Category
Documents
-
view
29 -
download
2
description
Transcript of Comparing film and video game reviews:
Comparing filmand video game reviews:
By Ben GiffordCleveland State University
December 7, 2011
A report using computer-aided text analysis
“Sometimes 'dead' is better”
E.T. the movie:Won 4 Oscars, nominated for another 5
E.T. the game:3.5 million unsold copies (out 5 million total) were allegedly buried in aNew Mexico landfill
- Jud Crandall, Pet Semetary (1989)
Background/Rationale
Video games are popular and the industry is wealthy
72 percent of American households play games
Average game player is 37, played for 12 years
$30.3 billion industry in 2006 $46.5 billion industry in 2009
Purchasing decisions
What makes people decide to buy games? Advertising Reviews Friends/Word of Mouth ??
Game reviews
Little-to-no research has been dedicated to video game reviews themselves
Are they “up to snuff?” Do they display critical thought?
Can they impact sales (future research) This project focused on comparing game
reviews to film reviews.
Similarities between media
Origins in “exciting spaces” Movies: kinetoscope parlors,
nickelodeons Games: arcades
Transitioned to home viewing/playing through VHS, television and home consoles/computers for games
Similarities continued
Focus on narratives One goal of both is to induce feelings of
presence Movies: sound, color, widescreen, high-
def surround sound, 3D Games: improved graphics, voice-acting,
motion capture, “natural”/motion controls, as well as 3D, surround sound, etc.
Film Reviews Early movie critics and reviewers came
from a theater background, and many early films resembled plays in the way they were shot and staged
Many notable film critics: Pauline Kael Roger Ebert Leonard Maltin
Game Reviews
Early game reviewers came from?? No truly famous game critics, at least not
by name
Comparing the Two
Scalzi (2006) points to the relatively young age of video games.
Games have only been at the point of telling stories for around 20-30 years.
It's only in the past 10-15 years that mae narratives have really evolved.
Comparing the Two Kael began writing for the New Yorker in
1967. She established a “golden age” for film
criticism. Film had already been around for 50-60+
years at the point Talkies had existed for about 40 years Narratives in films even before that
First Gaming Magazines
Both magazines launched in 1981. Computer and Video Games (U.K., left) still exists today but in a much different format and is primarily web-based.
Electronic Games Magazine
The chart above came from the first issue published in winter 1981 and compares the home consoles available at the time.
First video game reviews
Computer Gaming World also launched in 1981 and regularly reviewed computer games.It became Games For Windows in 2006, and shut down in 2008.
(First issue pictured)
First video game reviews
Famitsu began reviewing games in 1986 and is still well-regarded today.
It gave its first perfect score (40/40) in 1998 and has only given a total of 17 perfect scores in its 25 years of existence.
(First issue pictured)
Methodology
Using the popular review aggregator Metacritic (metacritic.com), 94 video game and 100 film reviews were gathered.
Reviews were selected using systematic random sampling and random.org
Sample Example
Make sure the proper filters are in place. This will show all of the reviews for PlayStation 3 games in descending order of Metascore
Pick a random starting point using random.org, based on sample size.
Sample ExampleNeed to see all the reviews that Metacritic has gathered
Pay attention the the Metascore – an average of all critics' scores
Sample ExampleScroll down and count all the reviews that are in line with the Metascore for that game.
If there are none, than count the ones closest distance wise (e.g. Metascore is 76, but no 76 reviews. Count all 77s and 75s if they exist. If not, count 78s and 74s, etc. until at least one review is counted)
Sample ExampleVisit random.org and enter the range with “1” as the minium and the number of reviews as the maximum. Red Dead Redemption had 11 reviews scoring a “95,” so enter “11” as the maximum.
Click “Generate.” Count that many down from the first review that was counted. That will be the data collected.
Sixth review from top scoring RDR at “95”
Click
Note: If a review is not written in English, or if a link is broken and that review cannot be found by searching the site and google, resample until a valid review is found.
Sample Example
Copy/paste whole review into a text file. Discard titles, subtitles, image captions, advertisements, ratings, and conclusions separate from review if any are present.
Note that some reviews may span multiple pages, requiring researcher to copy/paste each page in turn.
Sample ExampleReturn to master list of game or movie reviews
Count “X” reviews down from the previous item sampled, where “X” is “9” for PS3 games and “70” for movies.
Repeat the process over and over until the population lists are exhausted.
1
2
3
4
5
6
7
8
9
Coding
Reviews were coded using 12 dictionaries (8 Pennebaker, 4 custom) in Yoshikoder
Sample words
Cognitive Mechanics: abandon*, accept, accepted, accepting, accepts, achiev*, acknowledg*, adjust*
Film Genres: Action, Adventure, Biopic, Blaxploitation Chick Flick, Comedy, Crime, Detective, Disaster
Game Genres: 3PS, Action, Adventure, Arcade, Beat 'em Up, Beat em up, Dance, FPS, Fighter, Fighting
Negative Emotions: abandon*, abuse*, abusive, ache*, aching, advers*, afraid, aggravat*, aggress*
Sample Words Cont.Sample words
Nonsense: er, hm*, uh, um, umm*, zz*
Optimism: accept, accepta*, accepted, accepting, accepts, advantage*, adventur*, assur*, award*, best Referencing audience: thee, thine, thou, thoust, thy, Y'all, ya, ye, you, you'd, you'll, you're, you've, your*
Referencing self: I, i'd, i'll, i'm, i've, let's, lets, me, mine, my, myself, our, ours, ourselves, us, we, we'd,
Sample Words Cont.Sample words
Sensory: appear, appeared, appearing, appears, ask, Asked, asking, asks, ate, bitter*, call
Technical film terms: a-list*, a-movie*, accelerated motion, act, actor*, actress*, acts, ad lib, adaptation, Technical game terms: abstract game*, act, acts, adaptation, advergame*, aesthetic, allegor*, allusion*
Vulgarity: (use your imagination; they're all there)
More About Dictionaries
'Technical' Dictionaries Number of Entries
Film 309
Game 204
Overlap between the two
105
Genre Dictionaries Number of Entries
Film 39
Game 41
Overlap 3
Results
Cognitive Mechanics***
Optimism***
Negative Emotions*
Sensory Language
References to Audience***
References to Self**
Nonsense Words
Vulgarity
Film Genres***
Game Genres***
Technical Film Terms***
Technical Game Terms***
.0000 .0100 .0200 .0300 .0400 .0500 .0600
Mean Values For Average Language Use Across All Reviews
Movie Game
Average Language Use
Ca
teg
ori
es
* p < .05 ** p < .01 *** p < .001
Results
Cognitive Mechanics***
Optimism***
Negative Emotions*
Sensory Language
References to Audience***
References to Self**
Nonsense Words
Vulgarity
Film Genres***
Game Genres***
Technical Film Terms***
Technical Game Terms***
-1.000 -.800 -.600 -.400 -.200 .000 .200 .400 .600
Paired Samples Correlations
Between Medium and Dictionaries
Games Movies
Significant Results Tabled(Average language use)
Dictionary (Average) Games Movies Difference
Technical game terms .0420 .0169 .0251
Technical film terms .0154 .0274 .0120
Game genres .0039 .0013 .0026
Film genres .0021 .0049 .0028
References to self .0086 .0053 .0033
References to audience .0285 .0024 .0261
Negative emotions .0156 .0182 .0026
Optimism .0112 .0075 .0037
Cognitive mechanics .0491 .0405 .0086
MANCOVA Movie reviews collected were much shorter
than game reviews (word count)
Medium N Mean Median Std. Dev Min Max
Game 94 998.94 994.50 374.144 274 2052
Movie 100 464.61 419.50 291.621 52 1942
What if the word count restraints placed on movie reviewers affected writing style?
MANCOVA Tests of Significance
Only medium is significant
MANCOVA
Comparing new significant results to old ones
Dictionary (Average) Correlation squared (T-test)
Eta Squared (MANCOVA)
Technical game terms .608 .126
Technical film terms .219 .023
Film genres .096 .023
References to audience .659 .200
Using word count as a covariate really reduced variance explained by the significant variables
Discussion Problems
Yoshikoder Sampling
Future directions Financial impact of critical reviews Quanitfy differences between critcal
essays and reviews More dictionaries and improving validity
Fin