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AdamJMarsh commented on Accused of cheating, marathon runner Frank Meza's life fell apart (2019)   lamag.com/citythinkblog/f... · Posted by u/georgecmu
Ansil849 · 4 years ago
> Bodybuilding.com misc & 4chan are super toxic communities.

Yes, but so are Facebook and Twitter.

AdamJMarsh · 4 years ago
Communities there can and have been super toxic yes.

There is a difference though as those platforms have larger moderation resources though.

AdamJMarsh commented on Accused of cheating, marathon runner Frank Meza's life fell apart (2019)   lamag.com/citythinkblog/f... · Posted by u/georgecmu
dfgasdgsd · 4 years ago
This was such a sad story - everything I read at the time said Dr Meza was a charitable, successful member of the community in LA (running coach, founded programs towards Latino students, etc.).

The LetsRun forum is such a wild place - it's a really strange mix of great running news discussion, 4-chan / bodybuilding.com conspiracy theories, and (IMO) a lot of teenage / college male runners who have a lot of angst, and something to prove because they are in an unpopular sport. Moderators/owners (rojo / pojo? or something) don't do anything / actively encourage this.

AdamJMarsh · 4 years ago
Bodybuilding.com misc & 4chan are super toxic communities.

I look back at my teenage years and realised how hazardous they are to mental health. My curiousity & engagement on those communities was limited to infrequent lurking.

I now understand why alt-right/q anon movement popped up so quickly.

A big issue with these boards is that the ownership can't overmod because these communities are a big drawcard, even if they're financial negatives.

AdamJMarsh commented on Google mandates workers back to Silicon Valley, other offices from April 4   reuters.com/technology/go... · Posted by u/pseudolus
librish · 4 years ago
I think anyone who's claiming that remote work has been "proven" to be better or worse is wrong. There are some studies but they use estimations and proxies, carrying the same flaws as doing performance reviews based on lines of code.

We've proven that the big tech companies can go fully remote and not completely crash and burn, that's about it. Some people love the lack of commute and less semi-forced hanging out, some people hate onboarding on a new company as a remote person and so on and so on.

I personally prefer a company where everyone's on site. I want to be able to quickly resolve any issues in person, not over voice call or slack, and I think that an environment where someone can tap me on the shoulder when they need help leads to overall higher productivity, even if individual productivity suffers temporarily.

AdamJMarsh · 4 years ago
Except you're also affecting the individual productivity of others.

The tap on the shoulder is the most annoying thing working on site. There's no respect for the urgent & critical tasks.

You would want others to spend 2 hours commuting, wasting time on parking, food & fuel just to be able to physically speak to them.

What a waste of our current technological advantages.

Why bother working in tech, when you don't use it to better yourself and others?

AdamJMarsh commented on What I learned reviewing 35k reviews from Steam    · Posted by u/AdamJMarsh
magicalhippo · 4 years ago
I don't know much about PUBG, but I did play a lot of other online shooters. Based on those experiences it seems there's a fairly large number of players who thinks that anyone substantially better than them are cheating.

They played with poor sound setup so didn't realize I knew exactly where they were thanks to a good headset and could blast them in the face as they rounded that corner.

Or they didn't know about drag/flick shooting[1] so they thought the snap that landed the headshot was a cheat rather than a deliberate, physical mouse movement.

Or just they just significantly overestimated their own abilities, thinking anyone being that much better must be cheating.

[1]: https://themeta.com/aiming-essentials-3-flick-shot-technique...

AdamJMarsh · 4 years ago
This could be on the money here.

Interestingly, I recently read an article regarding the gaming in China.

Most video games were accessed pirated, with hacks built into the install. Not saying this is the case with PUBG, but it can explain why there is a higher distribution of hackers in some video games (namely CS Source).

AdamJMarsh commented on What I learned reviewing 35k reviews from Steam    · Posted by u/AdamJMarsh
AdamJMarsh · 4 years ago
GTA V

- Grand Theft Auto V had the 2nd highest amount of total reviews

- There 927 total negative reviews gathered (from clusters containing 193+173+164+130+124+31+113 negative reviews)

- There were 243 positive reviews (from clusters containing 54+43+27+22+15+58+24 positive reviews.)

- This gives it a rough ratio of 3.8 negative reviews for every 1 positive review. This was the largest amount in the dataset.

- A large number of complaints revolved around banning. Whether it was a general complaint on bans, unfair banning or the ban appeal.

- A large number of reviews were orientated around general mods references or specific mods. Words that came up were related around “mods” “modding” “openiv”

- Certain missions, vehicles, or purchases were mentioned such as “Royale” & “Alpha”

- There was a less quantity of negative reviews regarding hackers.

- There were a less quantity of negative reviews relating to microtransactions with specific mentions of “rockstar”, “greedy”, “gtx”, “currency”, “pay”, “paying” “overpriced”

Rocket League

- Rocket League had a total of 517 recommended reviews (in clusters of 49+351+117 ) to 10 not-recommended reviews (in clusters of 3+6+1).

- The largest cluster of reviews made specific references to “addictive” “addiction” “fun” as qualities of the gameplay.

- Many positive mentions of the game being “entertaining”, “fun” & “enjoyable”

Rust

- Rust had a distribution of 569 recommended reviews (from clusters of 64+323+182)

- It had a not recommended reviews of 103 not recommend reviews (from clusters of 34+52+17)

- Many references were made mentioning “cancer” with regards to the game itself or the community.

- Other references included “gaming” “gameplay” “ammo” “community” “Gamers” “ultimate” “simulator”

- This game received many mentions of other games including “skyrim”, “fortnight”, “battlefield”, “minecraft”

- Specific items or gameplay mechanics were mentioned like “Death” “health” “dying” “war” “toxic” “survival” “pain” “fire” “build” “nake” “run” “kills” “looting” “gunplay” “spawns”

Overall positive recommended reviews

- 378 recommended reviews skewed towards co-operative video games.

- The most positive and popular recommendations (within two clusters of 351 & 323 reviews) specifically referenced the video games gameplay.

- 129 positive reviews were made making general mentions of the video game as being fun to play (a large portion of these making specific reference to Rocket League)

The negative sentiment reviews gave much meatier insights though.

Overall negative sentiment reviews

- 204 negative reviews that were made in relation to bad game play or poor game play quality.

- In 193 reviews, users complained about being banned by Steam.

- 173 negative reviews were made with reference to “mods”. These reviews were related to mods causing bugs that made their game crash or become unstable.

- 159 users complained about experiencing lag and latency issues within multiplayer video games.

- 153 negative reviews blamed games for crashing and glitching that rendered them unplayable or disruptive.

- In two different clusters that contained 147 & 142 each, negative reviews were posted, voicing complaints regarding hackers, which is common in online multiplayer games.

If I had my time again, I would...

- Like to spend more time mining for insights

- Work on updating or scraping my own dataset with a larger and more updated dataset.

- Track which game developers as well as video games had the highest amount of negative reviews, positive reviews and positive to negative review ratios.

- Begin to visualise each genre of video game, their review totals, and negative to positive review ratios.

- Map out repeatable criticisms or issues with larger marquee games, over a wider & more up to date dataset. (i.e Specific mentions of Fortnite Skins being too expensive, or negative sentiment with reference to GTA V Shark Cards)

End Credits.

Source: https://www.kaggle.com/luthfim/steam-reviews-dataset

Tool for Visualisation and Analysis https://relevance.ai

For those that want to dive deeper or reproduce this experiment:

Broader Clustering results - https://cloud.relevance.ai/dataset/steam_reviews_35k_zerosho...

Game specific clustering results – https://cloud.relevance.ai/dataset/steam_reviews_35k_zerosho...

For those that know Python, how to reproduce: https://drive.google.com/file/d/11EAQN_xYhIBmjU0ItAs5hxvW0Al...

Cleaned dataset source – https://github.com/RelevanceAI/michelangiolo_experiments_rep...

u/AdamJMarsh

KarmaCake day67December 3, 2021
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