Inverse55%

5 Years Later, Netflix's Surprise Horror Hit Remains One Of Its Best-Ever Originals 80%

By James Grebey58%

7/18/2026, 10:00:24 PM

BS Summary: This article contains 29 faulty reasoning types, including Negativity Bias, Availability Heuristic, and Post Hoc (False Cause), with Hasty Generalization as the most egregious example at 27.2% saturation with 243 hits. Analysis detected 1,753 faulty-reasoning hits from 892 analyzed words, generating a BS Score of 71.3% and a BS Rank of 80% (4,480 of 21,886 articles). This article is worse (more manipulative) than 79.50% of the article peer group.

What's the best thing Netflix has ever made? 
You might point to some of their biggest shows, like <em>Stranger Things</em> or <em>Bridgerton</em>, or perhaps some of their most critically acclaimed films, like <em>Roma</em> or <em>The Power of the Dog</em>. 
There's a good case it's <em>KPop Demon Hunters</em>. 
All of those are defendable answers, but for three weeks during the early days of lockdown, the answer was unquestionably <em>Fear Street</em>, a trio of films based on <em>Goosebumps </em>author R. 
L. 
Stine's slightly more mature book series of the same name. 
<em>Fear Street Part One: 1994</em> hit Netflix on July 2, 2021 with the next two films, subtitled <em>1978</em> and <em>1666, </em>coming out the following weeks. 
(Today is the fifth anniversary of the trilogy-capper.) 
Though vaccines had become widely available, the lockdown was very much ongoing and the rise of the Delta variant that put a damper on "Hot Vax Summer" and drove many back inside where they needed something to watch. 
Even though there were some new releases, especially when HBO Max started putting new Warner Bros. movies on streaming the same day as their theatrical release, there just weren't as many shiny new films to watch as the moment called for. 
Enter the <em>Fear Streets</em>. 
Set in the perpetually unfortunate town of Shadyside, the first <em>Fear Street</em> was a throwback to '90s slasher movies  with a slightly, refreshingly modern sense of sexuality, since main characters Deena (Kiana Madeira) and Sam (Olivia Scott Welch) are ex-girlfriends and nobody in the small town seems especially scandalized by this. 
When Deena, Sam and their friends find themselves hunted by the resurrected masked murderers of Shadyside's bloody past, it sends them searching for the truth behind the town's curse. <em>Part Two: 1978</em> is an homage to sleepaway camp slashers like <em>Friday the 13th</em>, and Sadie Sink stars as a survivor of one of Shadyside's previous murderous incidents. 
The final act, <em>1666</em>, goes all the way back to the beginning, revealing the backstory of the so-called witch Sarah Fier who cursed the town in the Colonial Era. 
(It's like if <em>The Crucible</em> was a gruesome teenage murder romp.) 
A mid-film title card for <em>1994: Part 2 </em>brings things back to Deena and Sam's time and concludes the whole story. 
The <em>Fear Street</em> movies are not the highest levels of horror filmmaking. 
The craft is respectable rather than groundbreaking, and the movies are deliberately iterative of other horror titles (though they do distinguish themselves with the interconnective, decade-spanning narrative). 
What they are, though, are a ton of fun. 
Funny, self-aware, and boasting compelling characters and a few murders that are much gnarlier than you might expect, <em>Fear Street</em> feels like the sort of "better than it needs to be" film that Netflix can really knock out of the park when the streamer chooses to. 
(See: <em>Carry On</em>.) 
It's worth noting how, amusingly, with these three movies Netflix did something the streamer is loath to do in almost any circumstance: weekly releases. 
Netflix is committed to the binge model to the possible detriment of their shows' longevity, considering how weekly series like <em>Widow's Bay</em> and <em>The Pitt</em> can build hype and an audience while the majority of Netflix shows are a flash in the pan that rarely have legs beyond the weekend all the episodes dropped. 
With <em>Fear Street</em>, Netflix gave horror fans something to be excited about for next week. 
Having them all get dumped on the same day would've been too much content. 
Had they come out a year apart, which is typically around the fastest that film sequels normally come out, it's almost assured some of the audience might have forgotten what they liked about <em>Part One</em> and never fired up <em>Part Two</em>. 
But weekly releases made <em>Fear Street</em> a horror event for the better part of a month. 
There are some relics of lockdown that do not hold up when rewatched in less-viral times. 
The popularity of <em>Tiger King</em>, for instance, was clearly a sign of cooped-up madness rather than a reflection of that documentary series' quality. <em>Fear Street</em> still works. 
It's some of the most enjoyable original horror you'll find on the streamer to this day. 
Despite the success of <em>Fear Street</em>, Netflix hasn't tried to replicate the formula. 
A fourth movie, <em>Fear Street: Prom Queen</em>, came out in 2025. 
Unlike the previous three films, this was a standalone movie nestled into the same Shadyside community, detailing a series of murders at Shadyside High School's 1988 prom. 
The lack of connections to an overarching storyline immediately make <em>Prom Queen</em> less exciting than the other movies, but the bigger issue is that <em>Prom Queen</em> is quite bad on its own terms as a slasher. 
If the other movies were clever homages to past eras of horror, <em>Prom Queen</em> is a dull, uninspired recitation of '80s tropes. 
<em>Prom Queen</em>'s failure<em> </em>does nothing to diminish the <em>Fear Street </em>trio's crown. 
The ever-prolific Stine wrote dozens of <em>Fear Street </em>novels. 
There's no shortage of source material should Netflix want to expand on what's quietly one of the streamer's best franchises. 
The lockdown might have made those first <em>Fear Street</em> films especially welcome, but they'd still be a special, scary-fun treat if they came out tomorrow. 
All the <em>Fear Street</em> movies are streaming on Netflix. 
Article reasoning-pattern comparisonThis article: 0.0%James Grebey: 6.1%Inverse: 4.0%Confirmation Bias0.0%This article: 0.9%James Grebey: 1.0%Inverse: 0.8%Anchoring Bias0.9%This article: 17.3%James Grebey: 7.2%Inverse: 3.6%Availability Heuristic17.3%This article: 11.9%James Grebey: 1.1%Inverse: 1.5%Representativeness Heuristic11.9%This article: 0.0%James Grebey: 0.9%Inverse: 2.3%Hindsight Bias0.0%This article: 7.0%James Grebey: 4.1%Inverse: 2.8%Overconfidence Bias7.0%This article: 3.9%James Grebey: 8.3%Inverse: 4.7%Framing Effect3.9%This article: 0.0%James Grebey: 0.3%Inverse: 0.6%Loss Aversion0.0%This article: 0.9%James Grebey: 1.0%Inverse: 0.7%Status Quo Bias0.9%This article: 0.0%James Grebey: 0.2%Inverse: 0.5%Sunk Cost Effect0.0%This article: 5.5%James Grebey: 3.6%Inverse: 3.8%Optimism Bias5.5%This article: 1.3%James Grebey: 0.6%Inverse: 2.1%Pessimism Bias1.3%This article: 24.8%James Grebey: 8.6%Inverse: 8.7%Negativity Bias24.8%This article: 1.3%James Grebey: 0.2%Inverse: 0.6%Self-Serving Bias1.3%This article: 3.0%James Grebey: 0.4%Inverse: 1.1%Fundamental Attribution Error3.0%This article: 0.0%James Grebey: 0.3%Inverse: 0.2%Actor-Observer Bias0.0%This article: 0.0%James Grebey: 0.5%Inverse: 0.8%In-Group Bias0.0%This article: 0.0%James Grebey: 0.0%Inverse: 0.2%Out-Group Homogeneity Bias0.0%This article: 8.9%James Grebey: 7.4%Inverse: 5.4%Halo Effect8.9%This article: 0.0%James Grebey: 0.5%Inverse: 0.2%Horn Effect0.0%This article: 0.0%James Grebey: 0.0%Inverse: 0.0%Dunning-Kruger Effect0.0%This article: 6.7%James Grebey: 2.2%Inverse: 1.9%Recency Bias6.7%This article: 3.5%James Grebey: 1.6%Inverse: 0.8%Primacy Effect3.5%This article: 0.0%James Grebey: 0.0%Inverse: 0.1%Blind-Spot Bias0.0%This article: 0.0%James Grebey: 0.9%Inverse: 0.4%Ad Hominem0.0%This article: 0.0%James Grebey: 0.6%Inverse: 0.2%Straw Man0.0%This article: 4.4%James Grebey: 1.6%Inverse: 2.7%Appeal to Authority4.4%This article: 8.2%James Grebey: 2.8%Inverse: 2.1%False Dilemma8.2%This article: 0.0%James Grebey: 0.4%Inverse: 0.6%Slippery Slope0.0%This article: 0.0%James Grebey: 1.3%Inverse: 0.5%Circular Reasoning0.0%This article: 27.2%James Grebey: 11.7%Inverse: 8.0%Hasty Generalization27.2%This article: 0.4%James Grebey: 0.1%Inverse: 0.1%Red Herring0.4%This article: 0.0%James Grebey: 0.5%Inverse: 0.9%Bandwagon0.0%This article: 10.3%James Grebey: 5.8%Inverse: 4.2%Appeal to Emotion10.3%This article: 0.0%James Grebey: 1.2%Inverse: 1.1%Begging the Question0.0%This article: 14.9%James Grebey: 5.2%Inverse: 3.4%Post Hoc (False Cause)14.9%This article: 0.0%James Grebey: 0.0%Inverse: 0.0%Tu Quoque0.0%This article: 1.6%James Grebey: 0.2%Inverse: 0.5%Burden of Proof1.6%This article: 0.0%James Grebey: 0.3%Inverse: 0.1%Appeal to Nature0.0%This article: 1.2%James Grebey: 0.9%Inverse: 0.6%Composition/Division1.2%This article: 5.0%James Grebey: 1.2%Inverse: 1.3%Anecdotal5.0%This article: 1.3%James Grebey: 0.4%Inverse: 0.2%No True Scotsman1.3%This article: 13.2%James Grebey: 3.6%Inverse: 2.5%Ambiguity (Equivocation)13.2%This article: 0.0%James Grebey: 0.0%Inverse: 0.0%Gambler’s Fallacy0.0%This article: 0.0%James Grebey: 0.0%Inverse: 0.3%Middle Ground0.0%This article: 0.0%James Grebey: 0.1%Inverse: 0.1%Personal Incredulity0.0%This article: 0.0%James Grebey: 0.0%Inverse: 0.1%Special Pleading0.0%This article: 0.0%James Grebey: 0.0%Inverse: 0.1%Genetic Fallacy0.0%This article: 6.1%James Grebey: 1.3%Inverse: 1.6%Unattributed Quote6.1%This article: 0.4%James Grebey: 0.0%Inverse: 0.5%Quote-first Misdirection0.4%This article: 4.3%James Grebey: 25.5%Inverse: 21.3%Biased Writer Voice4.3%This article: 0.0%James Grebey: 3.6%Inverse: 1.5%Indoctrination0.0%This article: 0.0%James Grebey: 0.0%Inverse: 0.2%Politically Left Leaning Bias0.0%This article: 0.0%James Grebey: 0.0%Inverse: 0.0%Politically Right Leaning Bias0.0%This article: 1.0%James Grebey: 2.0%Inverse: 2.0%Attempt to Sell a Product or S…1.0%

892 words analyzed.

Speakers

1speaker8.7%attributed speech814writer words
Voice mapSelect a segment to jump to its words
Writer's voice • 13 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 31 words • 0.0% coverageWriter's voice • 1 words • 0.0% coverageWriter's voice • 10 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageWriter's voice • 8 words • 0.0% coverageWriter's voice • 38 words • 100.0% coverageWriter's voice • 41 words • 0.0% coverageWriter's voice • 4 words • 100.0% coverageWriter's voice • 52 words • 0.0% coverageWriter's voice • 57 words • 0.0% coverageWriter's voice • 29 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 21 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 46 words • 0.0% coverageWriter's voice • 3 words • 0.0% coverageWriter's voice • 24 words • 0.0% coverageNetflix • 54 words • 100.0% coverageNetflix • 15 words • 0.0% coverageWriter's voice • 14 words • 0.0% coverageWriter's voice • 41 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 16 words • 0.0% coverageWriter's voice • 13 words • 0.0% coverageWriter's voice • 11 words • 0.0% coverageWriter's voice • 27 words • 0.0% coverageWriter's voice • 36 words • 0.0% coverageWriter's voice • 22 words • 0.0% coverageWriter's voice • 12 words • 0.0% coverageWriter's voice • 9 words • 0.0% coverageWriter's voice • 20 words • 0.0% coverageWriter's voice • 25 words • 0.0% coverageNetflix • 9 words • 100.0% coverage
Selected voice

Netflix

100%flagged-word coverage
78 attributed words100% of attributed speech78% writer coverage
0%35.0%70.0%Unattributed Quote+69.2 ptsWriter: 0.0%Netflix: 69.2%69.2%Attempt to Sell a Product +11.5 ptsWriter: 0.0%Netflix: 11.5%11.5%Biased Writer Voice-4.7 ptsWriter: 4.7%Netflix: 0.0%0.0%Quote-first Misdirection-0.5 ptsWriter: 0.5%Netflix: 0.0%0.0%

Attribution is sentence-level. Pattern percentages are calculated only from words assigned to that voice.

Loading…
Loading…
Loading…

Analysis

Hover over highlighted words in the article to view the associated bias or fallacy analysis.