Data statistics interface-graphic and text analysis data interface

Data statistics interface-graphic and text analysis data interface

Xin public platform launched the invitation-based internal testing of the data interface on January 6, 2015. Through the data interface, developers can obtain data similar to the statistical module of the official website of the public platform but more flexible, and can also perform advanced processing as needed.

During the invitation beta test, in order to ensure service quality, the data interface is only open to third-party platform developers. You can become a third-party platform developer by accessing the WeChat Open Platform and authorizing the public account login. The third-party platform can help operators manage public accounts and help authorized public accounts call data interfaces. In the permission set division of the public account login authorization mechanism, the graphic analysis data interface belongs to the business notification permission set.

The time for opening the data interface to all public account developers will be notified separately.

Please note:

1. The database of the public account data on the interface side only stores data after December 1, 2014. Data before that date cannot be queried. Even if data is found, it is unreliable and dirty data.
2. After calling the interface to obtain data, developers should save the data in their own database, which will speed up the next user's access and reduce unnecessary losses in calling the interface on the WeChat side.

The graphic analysis data interface refers to the interface used to obtain the graphic analysis data in the data statistics module of the official website of the public platform. The specific interface list is as follows:

***Time span refers to the time range in which data can be obtained when an API is called. For example, ***Time span of 7 means that a maximum of 7 days of data can be obtained at one time. The actual value of access_token can be obtained through "Get access_token".
Interface call request description

The graphic analysis data interface (including all interfaces in the interface list) needs to POST the following sample data packet to the corresponding interface call address:

  1. {
  2. "begin_date": "2014-12-08",
  3. "end_date": "2014-12-08"
  4. }

Return Description

Under normal circumstances, the returned JSON data packet of the interface for obtaining the daily data of group text and picture messages is as follows:

  1. {
  2. "list": [
  3. {
  4. "ref_date": "2014-12-08",
  5. "msgid": "10000050_1",
  6. "title": "December 27 DiLi Daily",
  7. "int_page_read_user": 23676,
  8. "int_page_read_count": 25615,
  9. "ori_page_read_user": 29,
  10. "ori_page_read_count": 34,
  11. "share_user": 122,
  12. "share_count": 994,
  13. "add_to_fav_user": 1,
  14. "add_to_fav_count": 3
  15. }
  16. //The following will list all articles that have been read on that date (including only mass-sent articles) and the number of times they were read on that day.
  17. ]
  18. }

Under normal circumstances, the JSON data packet returned by the interface for obtaining the total data of group text and pictures is as follows (please note that in details, the corresponding value for each day is the total amount of the article up to that day (not the amount of the day)). In addition, it is necessary to pay attention to the difference between obtaining the daily data of group text and pictures (getarticlesummary) and obtaining the total data of group text and pictures (getarticletotal) as follows:

1. The former obtains data such as the number of times all articles that have been read on a certain day (including only mass-sent articles) were read on that day.
2. The latter obtains the total data of articles sent in batches on a certain day, from the date of mass sending to the date of interface call (but data is counted for up to 7 days after the date of publication). For example, if an article is sent on December 1st, and the number of readings on the 1st, 2nd, and 3rd after it is sent is 10,000 respectively, then the data obtained by getarticletotal is that the total readings from the time of sending to 24:00 on December 1st are 10,000, the total readings from the time of sending to 24:00 on December 2nd are 20,000, and the total readings from the time of sending to 24:00 on December 1st are 30,000.

  1. {
  2. "list": [
  3. {
  4. "ref_date": "2014-12-14",
  5. "msgid": "202457380_1",
  6. "title": "The Lost Painting on Malaysia Airlines",
  7. "details": [
  8. {
  9. "stat_date": "2014-12-14",
  10. "target_user": 261917,
  11. "int_page_read_user": 23676,
  12. "int_page_read_count": 25615,
  13. "ori_page_read_user": 29,
  14. "ori_page_read_count": 34,
  15. "share_user": 122,
  16. "share_count": 994,
  17. "add_to_fav_user": 1,
  18. "add_to_fav_count": 3
  19. },
  20. //All data whose stat_date matches "ref_date (mass mail date) to interface call date" (but only 7 days at most) will be listed later
  21. ]
  22. },
  23. //There will be data for group-sent articles whose ref_date (group-sent date) is between begin_date and end_date in the future
  24. ]
  25. }
  26.  
  27. Under normal circumstances, the returned JSON data packet of the interface for obtaining graphic and text statistical data is as follows:
  28.  
  29. {
  30. "list": [
  31. {
  32. "ref_date": "2014-12-07",
  33. "int_page_read_user": 45524,
  34. "int_page_read_count": 48796,
  35. "ori_page_read_user": 11,
  36. "ori_page_read_count": 35,
  37. "share_user": 11,
  38. "share_count": 276,
  39. "add_to_fav_user": 5,
  40. "add_to_fav_count": 15
  41. },
  42. //There will be data with ref_date between begin_date and end_date later
  43. ]
  44. }

Under normal circumstances, the returned JSON data packet of the interface for obtaining graphic and text statistics time-sharing data is as follows:

  1. {
  2. "list": [
  3. {
  4. "ref_date": "2014-12-07",
  5. "ref_hour": 1200,
  6. "int_page_read_user": 0,
  7. "int_page_read_count": 0,
  8. "ori_page_read_user": 4,
  9. "ori_page_read_count": 25517,
  10. "share_user": 4,
  11. "share_count": 96,
  12. "add_to_fav_user": 1,
  13. "add_to_fav_count": 3
  14. }
  15. //Subsequently, ref_hour will gradually increase to list the data for 24 hours a day
  16. ]
  17. }
  18.  
  19. Under normal circumstances, the returned JSON data packet of the interface for obtaining the picture and text sharing and forwarding data is as follows:
  20.  
  21. {
  22. "list": [
  23. {
  24. "ref_date": "2014-12-07",
  25. "share_scene": 1,
  26. "share_count": 207,
  27. "share_user": 11
  28. },
  29. {
  30. "ref_date": "2014-12-07",
  31. "share_scene": 5,
  32. "share_count": 23,
  33. "share_user": 11
  34. }
  35. //There will be data of different share_scene (sharing scenes) and data with ref_date between begin_date and end_date in the future
  36. ]
  37. }

Under normal circumstances, the returned JSON data packet of the interface for obtaining the daily data of picture and text sharing and forwarding is as follows:

  1. {
  2. "list": [
  3. {
  4. "ref_date": "2014-12-07",
  5. "ref_hour": 1200,
  6. "share_scene": 1,
  7. "share_count": 72,
  8. "share_user": 4
  9. }
  10. //There will be data of different share_scenes and data of increasing ref_hour later. Since the maximum time span is 1, ref_date is fixed here.
  11. ]
  12. }

<<:  Custom menu management-custom menu creation interface

>>:  Data statistics interface-message analysis data interface

Recommend

What is the difference between Douyin’s yellow car and a window display?

If you want to make good Douyin short videos , in...

In-depth analysis and market report on overseas influencer marketing

This report is produced by SocialBook, an America...

What is mathematical proof?

William Dunham, a historian of mathematics and Tr...

How do mini programs split? Tips for attracting 1,000+ new customers a day!

Recently, a friend asked me how to achieve explos...

How can you make more money than others by copying others?

Preface Wrong, let me ask you a question, how do ...

Poisoning the data: How are artists fighting back against AI?

The University of Chicago has recently developed ...