Show HN: Automated writing analysis of Twitter and Reddit feeds
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Show HN: Automated writing analysis of Twitter and Reddit feeds
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Re: Show HN: Automated writing analysis of Twitter and Reddit feeds
#2I made this over the last two days in Node.js. The analysis is still pretty simple, and I'd like to expand it over time. It updates every 30 minutes, and you can already see that there's some significant shifts in literacy between the daytime and very early morning.
I had originally started the project to grab Flesch-Kincaid grade levels, but it was taking me 45 minutes to analyze about 20 pages of comments, so I switched it out for Automated Readability Index.
I really wanted to include HN, as I feel it's in a period of social shift, but it wouldn't have the same sort of statistical significance due to its size (it would most likely just be meaningless jarring jagged lines across the graphs). If someone can think of a good way to include HN, I'm all ears. I'd also be interested in other methods of writing analysis that I could include.
Re: Show HN: Automated writing analysis of Twitter and Reddit feeds
#3I made this over the last two days in Node.js. The analysis is still pretty simple, and I'd like to expand it over time. It updates every 30 minutes, and you can already see that there's some significant shifts in literacy between the daytime and very early morning. I had originally started the project to grab Flesch-Kincaid grade levels, but it was taking me 45 minutes to analyze about 20 pages of comments, so I swi…
This is a cool idea. Did you account for the smaller amount of users at night vs day?
It might be even more interesting to do comparisons between subreddits and comparisons between hashtags or followers of certain figures.
Also do you have a link to the source?
Keep up the good stuff!
Re: Show HN: Automated writing analysis of Twitter and Reddit feeds
#4Quibble: I don't think I'd consider either "yea" or "anyways" misspellings per se, at least in informal chatting. "Anyways" is heard in some spoken dialects, so you'd expect it in written forms of the same dialects. And I think of "yea" (in modern usage) as a variant of "yeah", like "yah" is. All of them are phonetic spellings of dialectal versions of "yes" to begin with (along with "yep" and "yup" and such).
They don't, at least, seem in the same category as clear spelling errors like copyright/copywrite, or bureaucracy/beaurocracy.
Re: Show HN: Automated writing analysis of Twitter and Reddit feeds
#5I made this over the last two days in Node.js. The analysis is still pretty simple, and I'd like to expand it over time. It updates every 30 minutes, and you can already see that there's some significant shifts in literacy between the daytime and very early morning. I had originally started the project to grab Flesch-Kincaid grade levels, but it was taking me 45 minutes to analyze about 20 pages of comments, so I swi…
This is a cool idea. Did you account for the smaller amount of users at night vs day? It might be even more interesting to do comparisons between subreddits and comparisons between hashtags or followers of certain figures. Also do you have a link to the source? Keep up the good stuff!
Thanks. It compares misspellings to correct spelling counterparts (anyways:anyway), so that, in itself, should account for sample size changes in Twitter. The Reddit sample size (should) stay constant, as I'm grabbing /all/comments every 15 seconds, which from everything I've seen is about 3 times longer than it takes for it to turn over.
I have been thinking about subreddits and hashtags, but I'm not sure what would be interesting to people and still have enough statistical significance to update every half-hour/hour. If I were going to release this on Reddit, I'd have probably arranged it as a comparison between all the major subreddits. As for hashtags, their impermanence makes them a difficult measure.
I don't have the source up yet, but it's pretty simple. I just get the json output of /all/comments and get the Twitter streams for the words I'm checking with ntwitter and then do the basic math to analyze it every half hour. I render the page myself with the backlog of values and then send it updated info as I process it, so if you leave the page open, it should keep fresh.
Re: Show HN: Automated writing analysis of Twitter and Reddit feeds
#6I made this over the last two days in Node.js. The analysis is still pretty simple, and I'd like to expand it over time. It updates every 30 minutes, and you can already see that there's some significant shifts in literacy between the daytime and very early morning. I had originally started the project to grab Flesch-Kincaid grade levels, but it was taking me 45 minutes to analyze about 20 pages of comments, so I swi…
What exactly is Twitter sample size? If it means "the number of records processed", why does it vary over time?
One way to approach the "significance" problem for smaller communities like HN is to create larger bins of misspellings/correct spellings. However, I don't think you're going to see many "anyways" or "yea" on HN at all, much less significant fluctuations over time.
Finally, an interesting question might be to what extent individuals fluctuate in their ARI/FK levels in different contexts. What if a poster in /r/lolcats writes a very asinine comment but then goes five minutes later to /r/programming to speak intelligently. Or is it the case that an idiot is an idiot, regardless of context?
Re: Show HN: Automated writing analysis of Twitter and Reddit feeds
#7Quibble: I don't think I'd consider either "yea" or "anyways" misspellings per se, at least in informal chatting. "Anyways" is heard in some spoken dialects, so you'd expect it in written forms of the same dialects. And I think of "yea" (in modern usage) as a variant of "yeah", like "yah" is. All of them are phonetic spellings of dialectal versions of "yes" to begin with (along with "yep" and "yup" and such). They do…
I chose those two to start things off for two reasons: The first is that they stand out to me as pretty basic misspellings that don't appear in any sort of popular literature, so it speaks to someone's reading experience. You can take that for whatever importance it is to you, personally. The second reason is their frequency. If the unit of measurement was larger than a half-hour or hour, I could measure a bunch of other things (which I might still do). As it stands, anyway|anyways|yea|yeah occur 25k-70k times per 30 minutes.
Re: Show HN: Automated writing analysis of Twitter and Reddit feeds
#8There is somewhat of an incentive to consciously misspell words on Twitter to save characters which muddles potential analysis like this.
Admittedly that doesn't apply here with "anyways" but it perhaps does with "yea". Perhaps throw out tweets over a certain length?
Re: Show HN: Automated writing analysis of Twitter and Reddit feeds
#9I made this over the last two days in Node.js. The analysis is still pretty simple, and I'd like to expand it over time. It updates every 30 minutes, and you can already see that there's some significant shifts in literacy between the daytime and very early morning. I had originally started the project to grab Flesch-Kincaid grade levels, but it was taking me 45 minutes to analyze about 20 pages of comments, so I swi…
What exactly is Twitter sample size? If it means "the number of records processed", why does it vary over time? One way to approach the "significance" problem for smaller communities like HN is to create larger bins of misspellings/correct spellings. However, I don't think you're going to see many "anyways" or "yea" on HN at all, much less significant fluctuations over time. Finally, an interesting question might be…
Sample size is the anyway|anyways|yeah|yea instances. I get those as they get posted, so that's why it fluctuates with time. Since they're so commonly used, it should incidentally give you an idea of all of Twitter's load. I'm also grabbing some other words that I haven't implemented on the clientside yet, but I don't include them in the sample size.
HN comments tend to be more varied and sparse, so I think you're right that measuring yea:yeah, etc. wouldn't be too enlightening. That said, I've noticed a defined qualitative shift in HN comments over the past few months, and I'd like to develop ways of measuring that before they reach Reddit/Twitter levels.
As for your last point, I could track individuals but a relational comparison based off of /all/ data would be pretty difficult due to the number of comments vs. the few number of any individual's comments. Also, ARI isn't a great metric (hence me putting it in a tiny graph) because it measures chars instead of syllables. For example, "FFFFFUUUUUUUUU" has the same score as "constructivism".
Re: Show HN: Automated writing analysis of Twitter and Reddit feeds
#10There is somewhat of an incentive to consciously misspell words on Twitter to save characters which muddles potential analysis like this. Admittedly that doesn't apply here with "anyways" but it perhaps does with "yea". Perhaps throw out tweets over a certain length?
That's why I'm not relying on any single metric, as well as framing it in the context of time. If Justin Beiber asks his fans to vote yea or nay on something, it might mess up the yea:yeah metric, but it should eventually normalize, and while it isn't normalized, the anyways:anyway metric should still be fine (Unless JBeibs is asking his fans to vote yea or nay on naming his new album "Anyways").