Pulp Fiction

Film Information

Pulp Fiction is a 1994 American crime film written and directed by Quentin Tarantino, who conceived it with Roger Avary.[4] Starring John Travolta, Samuel L. Jackson, Bruce Willis, Tim Roth, Ving Rhames, and Uma Thurman, it tells several stories of crime in Los Angeles, California. The title refers to the pulp magazines and hardboiled crime novels popular during the mid-20th century, known for their graphic violence and punchy dialogue.

All information in this section came from Wikipedia.

Clip Information

Two hitmen, Jules and Vincent, come to an apartment to retrieve a briefcase for their boss, the gangster Marsellus Wallace, from a business partner named Brett.

Abbrev	Film	Clip Start	Clip Stop	Duration
PulpFiction	Pulp Fiction (1994)	00:14:25.600	00:18:18.600	229

Characteristic	Value
Format	MPEG-4
File Size	45.2 MiB
Duration	229.021
Frame Rate	23.976
Video Width	1920
Video Height	816
Video BitRate	1.5 MB/s
Audio Channels	2
Audio SamplingRate	22050
Audio BitRate	115.1 kB/s

Subtitles

The following wordcloud shows the words used in this clip, scaled by number of occurrences and colored by sentiment (orange = negative, green = positive, grey = neutral or unsure). The sentiment estimates in this plot are token-based and derived from the Bing lexicon. Note that the words have been stemmed and lemmatized and stopwords have been removed.

The following figure shows the estimated sentiment (VADER compound score) for each subtitle line (orange = negative, green = positive, grey = neutral or unsure).

The table below shows all subtitles in this clip with the start and stop time of each subtitle’s appearance in seconds.

Start	End	Subtitle
7.116	10.988	Hey, kids. How you boys doin'?
11.053	13.717	Hey, keep chillin'.
19.894	22.695	You know who we are?
22.764	26.727	We're associates of your business partner, Marsellus Wallace.
26.801	29.830	You do remember your business partner, don't you?
32.541	35.479	Now, let me take a wild guess here.
37.513	40.542	- You're Brett, right? - Yeah.
40.616	44.955	I thought so. You remember your business partner Marsellus Wallace,
45.020	46.852	don't ya, Brett?
46.922	48.584	Yeah, I remember.
48.657	52.996	Good. Looks like me and Vincent caught you boys at breakfast.
53.062	55.692	Sorry about that. Whatcha havin'?
55.764	57.734	Hamburgers.
57.800	61.901	Hamburgers! The cornerstone of any nutritious breakfast.
63.272	65.572	What kind of hamburgers?
65.571	67.444	- Uh, ch-cheeseburgers. - No, no, no.
67.443	70.615	Where'd you get 'em? McDonald's, Wendy's, Jack-in-the-Box?
70.613	73.414	- Where? - Uh, Big Kahuna Burger.
73.482	76.613	Big Kahuna Burger! That's that Hawaiian burger joint.
76.685	80.625	I hear they got some tasty burgers. I ain't never had one myself. How are they?
80.689	83.388	They're- They're good.
83.459	86.090	You mind if I try one of yours?
86.161	88.597	- This is yours here, right? - Yeah.
96.839	98.706	Mmmm.
98.774	101.906	This is a tasty burger! Vincent!
101.978	104.505	You ever had a Big Kahuna burger?
105.514	108.042	Want a bite? They're real tasty.
108.117	111.556	- I ain't hungry. - Well, if you like burgers, give 'em a try sometime.
111.620	115.458	Me, I can't usually get 'em 'cause my girlfriend's a vegetarian,
115.524	118.655	which pretty much makes me a vegetarian.
118.727	121.893	But I do love the taste of a good burger. Mmmm.
121.965	126.497	You know what they call a Quarter-Pounder with Cheese in France?
126.569	128.630	- No. - Tell 'em, Vincent.
128.704	132.735	- A Royale with Cheese. - A Royale with Cheese.
132.808	136.270	You know why they call it that?
136.345	139.408	Uh, because of the metric system?
140.482	143.784	Check out the big brain on Brett!
143.852	147.189	You're a smart motherfucker. That's right. The metric system.
149.525	151.654	- What's in this? - Sprite.
151.727	153.663	Sprite. Good.
153.729	157.601	You mind if I have some of your tasty beverage to wash this down with?
157.666	160.536	Go right ahead.
167.243	170.147	[ Slurping, Sighs ]
171.982	174.817	That hit the spot.
174.883	178.949	You. Flock of Seagulls. You know why we're here?
178.946	182.628	- Why don't you tell my man Vince here where you got the shit hid. - It's over-
182.625	186.224	I don't remember askin' you a goddamned thing!
189.933	191.731	You were sayin'?
191.800	193.861	It's in the cupboard.
196.639	199.611	N-No, the one by your kn-knees.
201.411	204.645	[ Pans Rattling ]
206.749	209.812	[ Rattling Continues ]
220.497	222.797	[ Hit Man ] We happy?
222.865	225.735	Vincent?
225.801	228.500	- We happy? - Yeah, we happy.
228.571	230.507	[ Sighs ]

Holistic Ratings

A total of 104 participants watched this film clip and then provided holistic ratings on how the entire clip made them feel. These holistic ratings were completed using five Positive Affect items (i.e., alert, determined, enthusiastic, excited, inspired) and five Negative Affect items (i.e., afraid, distressed, nervous, scared, upset), each rated on an ordinal scale from 0 to 4. The plot below shows the distribution of scale scores (boxplot plus individual ratings).

Dynamic Ratings

A total of 104 participants watched this film clip and used the CARMA software to provide continuous (i.e., second-by-second) ratings of how it made them feel. These continuous ratings were made on a single emotional valence scale ranging from -4 (very negative) to 4 (very positive).

Chromodoris Plot

We can plot the distribution of all valence ratings per second of the film clip to get a sense of how its emotional tone changes over time. The solid black line represents the mean of all ratings and the yellow, green, and purple ribbons represent the central 50%, 70%, and 90% of the ratings, respectively.

Inter-Rater Reliability

Warning: There were 6 transitions after warmup that exceeded the maximum treedepth. Increase max_treedepth above 10. See
https://mc-stan.org/misc/warnings.html#maximum-treedepth-exceeded

Warning: Examine the pairs() plot to diagnose sampling problems

A Bayesian generalizability study was used to decompose the variance in ratings of this video clip into the following components: timepoint variance (in average ratings of each second, across raters), rater variance (in average ratings from each rater, across seconds), and residual variance (including second-by-rater interactions and measurement error). The lower and upper columns in the table below represent the boundaries of the 95% equal-tail credible interval. Note that we dropped the first 10 seconds of each clip (as rater “warmup” time).

Component	Term	Estimate	Lower	Upper	Percent
Rater	Variance	1.347	1.070	1.854	0.626
Timepoint	Variance	0.135	0.112	0.166	0.062
Residual	Variance	0.672	0.660	0.685	0.312

From these variance components, we can estimate inter-rater reliability of the ratings. There are many formulations of the two-way intraclass correlation (ICC), but the most relevant to our purposes here are the balanced average-measures consistency formulation or ICC(C,k) and the balanced single-measures consistency formulation or ICC(C,1).

Term	Estimate	Lower	Upper	Raters	Error
ICC(C,1)	0.166	0.142	0.198	1	Relative
ICC(C,k)	0.955	0.945	0.963	104	Relative

Below, we can also visualize the posterior distributions of each of these parameters. Values with higher posterior density are more probable.