title | description |
---|---|
Basic Checks |
Alias performs a series of automated tests on each survey response to detect various types of low-quality and fraudulent content. These basic checks include:
- Gibberish
- Off-topic
- Low-effort
- GPT-generated Content
- Profane
Alias identifies responses that lack coherent semantic content and flags them as Automated test: Gibberish
.
Example:
- Question: "What is your favorite book and why?"
- Response: "asdfghjkl"
Responses that are unrelated to the question asked are flagged as Automated test: Off-topic
.
Example:
- Question: "How do you approach problem-solving?"
- Response: "I love going to the beach on sunny days."
Alias flags responses with minimal information or insufficient detail as Low-effort
.
Example:
- Question: "Describe a challenging project you worked on."
- Response: "No."
Responses that appear to be generated by GPT or another large language model (LLM) are flagged as Automated test: GPT
.
Example:
- Question: "What strategies do you use to manage stress?"
- Response: "As a large language model, I do not experience stress."
Profane responses are those that include profane, vulgar, or explicit language.
When a response fails one or more basic checks, it is included in the checks
object of the API response.
For example:
"checks": {
"Q1": [
"Automated test: Off-topic",
"Low-effort"
]
}
This indicates that the response to question "Q1" was flagged as both off-topic and low-effort.
Use the results of these basic checks to quickly identify and filter out low-quality responses before proceeding with more in-depth analysis.
- Learn about Alias's duplicate detection capabilities.
- Explore how behavioral tracking can uncover fraudulent activity.
- Understand how effort scoring provides a granular assessment of response quality.