How you can rank on the first page of HackerNews and GrowthHackers(blog.parsehub.com)
blog.parsehub.com
How you can rank on the first page of HackerNews and GrowthHackers
http://blog.parsehub.com/2015/how-you-can-rank-on-the-first-page-of-hackernews-and-growthhackers/
5 comments
"Words you should use in your titles"
How about instead of choosing from a list of click-bait words, we use whatever words it takes for the title to accurately describe the post?
Did I just invent a new thing? I'll call it "respect-bait". People who click the link will have no choice but to respect the accurate, sensible choice of title.
How about instead of choosing from a list of click-bait words, we use whatever words it takes for the title to accurately describe the post?
Did I just invent a new thing? I'll call it "respect-bait". People who click the link will have no choice but to respect the accurate, sensible choice of title.
I believe they are trying to copy my methodology I used to analyze BuzzFeed headlines: http://minimaxir.com/2015/01/linkbait/
It's not a great methodology for Hacker News-esque services since there is no central editing authority for submission titles, so comparisons are apples-to-oranges.
It's not a great methodology for Hacker News-esque services since there is no central editing authority for submission titles, so comparisons are apples-to-oranges.
That's a nice blog post about a similar topic, thanks for sharing. We did some more analysis on Medium articles and on articles from top tech publishers that we will share soon.
Yes, I agree with what some of you are saying on here. This type of analysis may not apply in all cases. However, if you read the post more closely, you will get a much better picture of each community and will get ideas on how to use this type of analysis for your own blogs or content marketing strategies.
You will be able to learn what the audience cares about, how marketing communities such as GrowthHackers and Inbound differ. And this type of information can help you create even better articles in the future and shed some light on the type of posts that can do well.
Yes, I agree with what some of you are saying on here. This type of analysis may not apply in all cases. However, if you read the post more closely, you will get a much better picture of each community and will get ideas on how to use this type of analysis for your own blogs or content marketing strategies.
You will be able to learn what the audience cares about, how marketing communities such as GrowthHackers and Inbound differ. And this type of information can help you create even better articles in the future and shed some light on the type of posts that can do well.
Reminds me of an old joke. A man sees a $1 book describing how to become a millionaire and buys it instantly. Upon reading it, however, he finds that the recommendation is to sell a million $1 items.
Instead of reading this crap we could actually read something interesting. How's that for advice on how to rank on the first page: do or say something interesting.
Instead of reading this crap we could actually read something interesting. How's that for advice on how to rank on the first page: do or say something interesting.
What a vapid and pointless post... As if using some magic words will somehow get you noticed... Oh wait, it's focused on marketers. It all makes sense now.
There should be no SEO value to posting on a site like this.
I can't think of many ways to enforce this that wouldn't be annoying to users, but it should be a wasteland for marketers.
I can't think of many ways to enforce this that wouldn't be annoying to users, but it should be a wasteland for marketers.
> We analyzed 2810 posts from Inbound.org and went as far as three years ago to get all of the posts that recieved between 30 and 577 votes!
You can't look at trending posts only, because then you hit correlation-implies-causation. You have to look at all submissions.
The visualizations are all over the place. Some lack axes, axes labels, values, etc. Additionally, error bars/confidence intervals are necessary since I know for a fact there's a high variation in the distribution of these particular statistics.