Data collection is a very broad concept that can refer to any process of obtaining data from external sources. This data can come from a variety of different sources, including real-time sensor readings, website traffic logs, transaction records from shopping sites, posts and comments on social media, and more.
For live streaming, data collection is very important as it helps us understand how the stream is functioning, as well as the preferences and behavior of the viewers/users. By analyzing the data, we can identify problem areas and come up with rationalized solutions. Additionally, data analysis helps us predict future trends, which in turn helps us make informed decisions.
If you want to start capturing live streaming data, then you need to start by defining the type of data you want to capture and the relevant information. For example, if you want to understand the live stream traffic, then you need to get the live stream log files first. And if you want to understand the behavior of the user/viewer, then you need to first get the cookie file generated when the user/viewer uses the live room.
2: Principles of data collection
Live streaming data collection is the process of acquiring data by monitoring the live streaming room in real time. It includes data collection on the real-time status of the live streaming server, live content, and viewer behavior.
Through the data collection of live content and viewer behavior, you can understand the operation of the live room, so as to develop a reasonable operation strategy.
The data collection of the content of the live room mainly includes the analysis of the video files stored on the live streaming server, the analysis of the content of the program that is being broadcasted, and the review and analysis of the content of the program that has ended.
3: Ways of data collection
There are various ways to collect data in the live room, such as monitoring the live content through a watchdog program, or using a questionnaire to understand the audience's feedback. Regardless of the approach, you need to consider how to ensure the accuracy and reliability of the data.
Among them, the watchdog program is a common way of data collection. Through the watchdog program, live content can be monitored in real time and the data can be analyzed. For example, in a watchdog system, for a 3-hour live content, the content can be categorized based on different keywords. Additionally, a large amount of data about viewer preferences, engagement, and interaction can be obtained through a watchdog system.
However, there are some risks associated with using a watchdog system. First, failure to use a watchdog system correctly can result in inaccurate data collection or the omission of important information. Additionally, because watchdogs record and store large amounts of data locally, they pose a threat to personal privacy if stolen or leaked.
Therefore, it is important to do a good job of risk assessment when using the watchdog method for data collection. The risks associated with the reasonable use of watchdog methods for data collection can be avoided. As long as the accuracy and security of the data can be guaranteed.
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1: Introduction to UDI acquisition
Live broadcast data acquisition is a very important task, which can help us to understand the operation of the live broadcast, and make decisions for the operation of the live broadcast. In this article, we will introduce how to use the UDI tool to collect live room data.
UDI (Universal Data Collector) is a data collection tool developed by Aliyun, the big data platform of Alibaba Group. It helps developers efficiently collect data in various formats and analyze, store and display the data.
Before using UDI to collect data from live broadcasts, we need to understand the basic principles of UDI, which is a distributed system that contains three parts:
For live broadcasts, we can use UDI to collect information about traffic, pop-ups, and the number of people online. By analyzing this information, we can understand the operation of the live room and make decisions for the operation of the live room.
2: Introduction to data export
Live room data collection refers to the acquisition of live room data through various ways. The data source can be the API of the live broadcast platform or a third-party data collection tool. The data includes live streaming traffic, pop-ups, chat room information and so on. This data can help the owner of the live broadcast to analyze the content, understand the audience preferences, and then develop a reasonable live broadcast plan, reduce the cost of live broadcasts, and increase the quality of live broadcasts.
There are many ways to export live data, and the common ones are manual export and automatic export. Manual export needs to take the initiative to collect data in the live room, usually need to use specific tools, such as Excel, Google Sheet and so on. Automatic export, on the other hand, is realized through the platform or third-party tools, and generally speaking, there will be certain rules and restrictions on the use.
For individual users, manual export is a good choice because it allows data collection at any time according to their needs. For enterprise users, such as live streaming platforms, content production companies, advertising companies, etc., automatic export is usually chosen to capture a large amount of data.
Regardless of which method is used to export data, it is important to pay attention to data preservation and backup issues.
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3: Delete fan attributes
The live broadcast data collection is divided into three steps: deleting fan attributes, collecting live broadcast data, and analyzing live broadcast data.
In the step of deleting fan attributes, you can use the api of the third-party platform to select fan attributes based on keywords. The api of the platform will match the fan attributes corresponding to the keywords and return the top few fans with the highest match.
Collecting live broadcast data is generally realized by api, the live broadcast platform will open api to developers for developers to call. Common live data are the number of live online, the number of pop-ups, the number of likes, the number of shares and so on.
The last step is to analyze the live broadcast data.