I was wondering if anyone knew what is the max number of LinkedIn connection a user can add per day?
Thanks!
the maximum number of linked-in request per day is 50 on single day, previous it was 300 then year by year they reduced. if you are a premium user then there is no restriction in request only in mails restriction are there. if you logged as normal user then its 50.
https://www.linkedin.com/pulse/how-get-around-new-linkedin-connection-request-limit-2021-alex-gray/ says it's probably ~100 per week.
https://evaboot.com/blog/how-many-connection-requests-send-on-linkedin and https://expandi.io/blog/linkedin-connections-limit/ and https://www.paulgreensmspmarketing.com/the-new-linkedin-connection-request-and-what-it-means-for-msps/ seem to agree.
And the last one says there is an "ultimate cap of 30,000 connections".
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I am trying to find the top most followers based on the number of tweets about a brand named Maybelline on Twitter. The brand has about 600K followers and when I try to retrieve them the code keeps running for hours. So is there an efficient way to do this? I am using the below code after setting up twitter authentication. I want all the followers ( top 50) who tweeted the most about Maybelline.
user<-getUser('Maybelline')
user$toDataFrame()
followers<-user$getFollowers()
Thanks
While working with the Twitter API, it's useful to familiarize yourself with their limits. You have two main limits for a GET request, one is a Rate Limit (how many requests you can make in a 15 minute timeframe) and the other is the limit of how many results a certain call gives you.
In your scenario, you are using the GET followers/list endpoint from their API. You can read the docs for that here. That endpoint returns a list of followers and is limited to 20 followers per request and 15 request per 15 minutes, meaning that in a 15 minute timeframe, you can only retrieve 15*20 = 300 users. So to retrieve 600K followers that would take a very long time ( 30K minutes = 500 hours = ~21 days ).
It would be more efficient to use the GET followers/id which returns up to 5K user ids with each request with the same 15 request per 15 minute rate limit. Twitter API reference here. You can use this in conjunction with the Twitter GET users/lookup which returns up to 100 users per request and has a rate limit of 900 requests per 15 minutes. This means it would take 2 hours (at 75K users per 15 minute increment) to get 600K followers id's. And less than 2 hours to get the user objects ( at 90K users per 15 minutes ).
The rate limits can change depending on how the package you are using does authentication. If you are logging in as a Twitter user with your credentials, then the above rate limits are correct. If you are using only application credentials, then getting the followers will take 3x longer as users/lookup has a rate limit of 300 requests in that case or 30K users per 15 minutes. This answer has some good information on rate limits.
If you refer to http://www.google.com/intl/en_uk/analytics/premium/features.html, you will notice that Standard allows for 10 million hits processed per month and Premium allows for 1 billion.
I have a website on an account, with multiple "folders" for different sub-domains, and also different "Views" or dashboards for some of these sub-domains.
The website I am on recently lost tracking for conversion rates, and everything has plummeted to near 0%, which is an incorrect statistic. I am curious as to how I can figure up if this account is reaching the 10 million limit on the standard version. Or at least how to figure actual hits processed a day, week, or month?
Any ideas?
Thanks!
I don't know how Google enforces hit limits in 2015. However in 2013 a Google representative sent one of our bigger clients a document (answering a question about data limits) that contained the following paragraph:
How do data limits impact sampling? Google Analytics does not sample
your clients data at the point of collection or processing, regardless
of how far they exceed our stated limits. So no hits are discarded.
The only way to sample data at the point of collection is for clients
to use_setSampleRate in their tracking code.
[...]
[...] we reserve the right to shutdown their account [sc. if limits are exceeded], but it won't
happen before we have attempted to contact the account Admins multiple times
and we have exhausted all other options.
Unless Google has changed it's policy in the last 1,5 years I would say not, unprocessed hits are not your problem; it seems Google would have contacted you with an request to limit your hits or upgrade to Analytics Premium before problems occurr.
Plus, since you mentioned that you have several views - views do not count towards your quota (they display the same data in different ways). However properties (I think that is what you mean by "folders") do.
Updated 2017: It seems that Google intends to enforce limits more strictly. One of my clients now has the following warning in his GA interface:
Your data volume (XXX hits) exceeds the limit of 10M hit per month as
outlined in our terms of service. If you continue to exceed the limit
you will lose access to future data.
You can create a database table, like this:
visits(
id bigint primary key auto_increment,
ip text,
visit_date timestamp default current_timestamp
)
Upon each page visit, you can insert a record into the table. Later you can view statistics. For instance, visit count in a given day would look like:
select id, ip, visit_date
from visits
where visit_date >= '2015-07-21 00:00:00' and visit_date < '2015-07-22 00:00:00'
We've noticed lately that as our site is growing, our data in Google Analytics is getting less reliable.
One of the places we've noticed this most strongly is on the "Realtime Dashboard".
When we were getting 30k users per day, it would show about 500-600 people on line at a time. Now that we are hitting 50k users per day, it's showing 200-300 people on line at a time.
(Other custom metrics from within our product show that the user behavior hasn't changed much; if anything, users are currently spending longer on the site than ever!)
The daily totals in analytics are still rising, so it's not like it's just missing the hits or something... Does anyone have any thoughts?
The only thing I can think of is that there is probably a difference in interpretation of what constitutes a user being on line.
How do you determine if the user is on line?
Unless there is an explicit login/logout tracking, is it possible that it assumes that a user has gone if there is no user generated event or a request from the browser within an interval of X seconds?
If that is the case then it may be worth while adding a hidden iframe with some Javascript code that keeps sending a request every t seconds.
You can't compare instant measures of unique, concurrent users to different time-slices of unique users.
For example, you could have a small number of concurrent unique users (say 10) and a much higher daily unique users number like 1000, because 1000 different people were there over the course of the day, but only 10 at any given time. The number of concurrent users isn't correlated to the total daily uniques, the distribution over the course of the day may be uneven and it's almost apples and oranges.
This is the same way that monthly unique and daily uniques can't be combined, but average daily uniques are a lower bound for monthly uniques.
I check my Google analytics on a regular basis to obviously see my daily hits and for some reason my UNIQUE VISITORS count dropped from 1770 to 1730 over a day. How this is possible?
I started to notice this about a week ago when I saw that my UNIQUE VISITORS count wasn't going over 1800 (which it should have considering the visits I receive). I receive an average of about 60 unique VISITS a day but even if it was 0 unique visits a day, it doesn't sound logical that my overall UNIQUE VISITORS count would drop.
Now I can't take GA seriously anymore ...
Anyone have this problem before and / or could shed any light on the matter?
The statistics are period based. When a day passes, the period (begin and end) advances a day as well. So is perfectly normal your total unique visits changes from one day to another, because the period changed too.
For example: lets suppose your site receive 60 unique visitors every single day. You check your Analytics today (13-08-2012) and see 1860 visits. That amout is the total unique visitors for the period from 13-07 until 12-08.
But lets say that your site receives only 10 visitors today. Tomorrow (14-08) you will see your total unique visitors drops from 1860 to 1810, because the period will be from 14-07 until 13-08.
GA Unique Visitors data isn't making sense to me. From the GA FAQ we get the following definition for 'Visits vs. Visitors'
"The initial session by a user during any given date range is considered to be an additional visit and an additional visitor. Any future sessions from the same user during the selected time period are counted as additional visits, but not as additional visitors. "
The part that I can't resolve with the GA graph is "Any future sessions from the same user during the selected time period are counted as additional visits, but not as additional visitors". For the graph below covering a 30-day period, I would understand the GA definition to mean that the data represents uniqueness across all 30 days, right? But if you look at the screen shot below, you see a regular pattern for each week over the 30-day period the report covers. From that, it seems the numbers we are seeing associated with each of the days of the graph (e.g. 3.92% (4142) for Tuesday, September 8) is a count of unique visitors just in the context of that one day - i.e. without correlating their uniqueness to the rest of the days in the 30-day period. If the graph actually showed uniqueness across the 30-day period, I would expect the daily numbers to start high in the early days of the period and decrease over the 30-day period as the number of already-seen visitors (i.e. returning visitors) increases, no?
What am I missing here?
UPDATE
Helpful clue from Jonathan S. below got me on the right track.
I think I understand now what the daily bar graph values mean, but it's a little counter-intuitive and I'd bet not what some others might be assuming as well. The reports states "39,822 Absolute Unique Visitors" at the top, which means just that: over the 30-day period we saw this many uniques. Fair enough. The confusing part is that the daily (or weekly) bar values in the graph below are not mutually exclusive uniques as I had assumed, but are values relative only to the 39,822 total - i.e. there is overlap between the unique visitor counts across any group of days. This means the sum of the daily % values > 100% and the sum of the daily count values > 39,822. The algorithm is: when you visit for the first time in the 30-day period, call that "today", you add 1 to the total (39,822) and 1 to the "today" bar value. When you show up again "tomorrow", you are NOT counted again in the total, but ARE counted as 1 in the "tomorrow" bar value.
alt text http://img.skitch.com/20090922-djti81ejj5gqn575ibf8cj1e8x.jpg
I believe it's just an issue of grouping. The top right of the graph has 3 icons to group by day, week, or month. It's currently grouping by day. So if I visit your site today and come back tomorrow, I'll be counted once for each day.
I tried looking at the month view for one of my sites but it didn't give me much meaningful data. I believe the above should answer your original confusion though.
Is it possible that you're searching for something what isn't existing anymore? Unique Visitors/Visits is old terminology. Check: https://www.seroundtable.com/google-analytics-sessions-users-18424.html
Then check how sessions and users are defined:
Sessions ("ex-visits", it's very detailed): https://support.google.com/analytics/answer/2731565?hl=en&ref_topic=1012046
Users in Google Analytics reporting are defined as "Users who have initiated at least one session during the date range". So IMHO it's not about 30 days, it's about the SELECTED date range.
I hope this helps.