Definition of Breidbart Index
The Breidbart Index (BI) is a mathematical formula used to determine the level of spamming in Usenet newsgroups and other online discussion forums. It calculates the “spam score” of a particular message based on the number of newsgroups it is posted to and the number of times it is repeated within a specific timeframe. A higher BI score indicates a higher likelihood that the message is spam.
The phonetics of the keyword “Breidbart Index” is: /’breɪdbɑrt ˈɪndɛks/.
- The Breidbart Index calculates the total impact of spam or excessive cross-posting on Usenet, providing a metric for controlling the spread of unwanted messages.
- It uses a formula that considers the number of newsgroups the message is posted to and applies a score based on a logarithmic scale, penalizing posts to too many newsgroups.
- If a message’s Breidbart Index exceeds a predetermined threshold (typically 20), measures can be taken to cancel the message on Usenet or hold the user responsible for their actions.
Importance of Breidbart Index
The Breidbart Index is an important technology term because it serves as a quantitative measure to identify and combat spam and unwanted messages on online forums, specifically in the Usenet system.
Devised in the early 1990s by Seth Breidbart, this index was designed to facilitate spam detection by calculating the total “value” of an article based on its rate of cross-posting to multiple newsgroups.
By assigning a numeric value to each post, administrators could easily determine if a post exceeded a certain threshold, deeming it as spam and taking appropriate action to remove it.
The Breidbart Index not only helped in keeping discussions spam-free, but also contributed to maintaining the overall usability and relevance of online forums for their users.
The Breidbart Index, developed by Seth Breidbart, serves a fundamental purpose in the world of online discussion groups and forums—specifically, those that use the Usenet system. The primary aim is to manage the proliferation of spam and unwanted messages in these communities.
It achieves this by quantifying the spread of a single message across multiple newsgroups using numerical values, which eventually aids in the identification of mass-posted messages. Although it was created in the 1990s, the Breidbart Index remains relevant in various moderated discussion groups and online communities, helping create a more streamlined user experience and preventing the clogging of forums with repetitive or unwanted content.
The Breidbart Index is employed by several news administrators and moderators as a rule of thumb to efficiently determine whether a message is considered spam. By calculating the weighted sum of crossposts based on the Breidbart Index algorithm, moderators can identify which messages cross a predetermined threshold, signifying it as spam.
Consequently, these messages may be deleted or users posting such content banned. Effectively, the Breidbart Index contributes to maintaining a high-quality information exchange and prevents the abuse of resources for promotional, disruptive, or irrelevant purposes, thus fostering an organized and user-friendly environment for online discussion and interactions.
Examples of Breidbart Index
The Breidbart Index is a technology developed by Seth Breidbart in the early 1990s, designed to detect and measure spam on Usenet newsgroups. Although the technology is primarily associated with Usenet, its principles can be applied to other contexts. Here are three real-world examples related to the Breidbart Index:
Usenet Anti-Spam Measures:The Breidbart Index was originally designed as an anti-spam tool for Usenet. It measures the distribution of a message across multiple newsgroups by assigning each cross-post a weightage. A higher Breidbart Index indicates higher likelihood of a message being spam. This technology allowed system administrators and moderators to automatically identify and filter spam, thereby improving the quality and usability of Usenet newsgroups.
Mailing List Management:The principles of the Breidbart Index can be applied to mailing list management to ensure that subscribers receive relevant emails only. By tracking and analyzing the frequency of cross-posting among various mailing lists, administrators can identify and block spammers or remove irrelevant content. This enhances the overall experience for users who rely on mailing lists for valuable information, discussion, or collaboration.
Social Media Algorithms:While the Breidbart Index was specifically developed for Usenet, similar strategies can be used in social media platforms to identify and filter spam. For instance, if a user shares identical content across multiple groups or communities, this behavior can be assigned a weightage based on the principles of the Breidbart Index. While not a direct application of the technology, the concept can be integrated into social media algorithms to improve the quality of shared content and fight against spam.
Breidbart Index FAQ
1. What is the Breidbart Index?
The Breidbart Index is a measurement used to determine the amount of spam posted in Usenet newsgroups. It’s calculated based on the number of newsgroups the spam is posted to and takes into consideration the cross-posting of messages.
2. Why was the Breidbart Index created?
The Breidbart Index was created as a tool to help manage and control the increasing amount of spam in Usenet newsgroups. It was designed to provide a standardized measure to identify and handle spam efficiently and fairly.
3. How is the Breidbart Index calculated?
To calculate the Breidbart Index, you take the sum of the square roots of the number of newsgroups each spam article is posted to over a 45-day window. If an article is posted to 9 newsgroups, its Breidbart Index is the square root of 9, which is 3. If another article is posted to 16 newsgroups, its Breidbart Index is 4. The total Breidbart Index in this example would be 7.
4. What is the significance of a high Breidbart Index?
A high Breidbart Index indicates that an individual or group is posting a large volume of spam across multiple newsgroups. Internet Service Providers and Usenet administrators use the Breidbart Index to identify and take action against spammers, including cancelling spam posts or banning the spammer’s account.
5. Can the Breidbart Index be used to combat spam today?
While the Breidbart Index was an effective measure to combat Usenet spam in the past, its relevance has lessened with the decline of Usenet usage. However, some of its principles could be adapted to other spam-fighting methods and platforms like email and forums. It serves as an important historical development in the effort to manage and control spam online.
Related Technology Terms
- Spam threshold
- Spam detection
- Message cross-posting
Sources for More Information
- Wikipedia: https://en.wikipedia.org/wiki/Breidbart_Index
- J.D Falk’s Introduction to the Breidbart Index: http://www.panix.com/~jdfalk/html/breidbart.html
- The Spamhaus Project: https://www.spamhaus.org/whitepapers/mailing_list_standards/DNSBL_Usage_Breidbart_Index.pdf
- WinGate Proxy Server: https://www.wingate.com/knowledgebase7676.aspx