How can the concept of an emotive conjugation be extended into an orthogonal dimension?
And got the quite good answer:
Emotive conjugation can be extended into an orthogonal dimension by considering the emotional valence of the conjugated words, as well as their emotional intensity or magnitude. This creates a two-dimensional emotional space that captures the range of emotions that can be expressed by a given word or phrase.
For example, we can use the emotional valence of words along the vertical axis of the emotional space, where positive emotions are at the top, neutral emotions are in the middle, and negative emotions are at the bottom. The emotional intensity of words can be placed along the horizontal axis, where low emotional intensity is on the left and high emotional intensity is on the right.
By placing different words in this emotional space, we can visualize the range of emotions they convey, and how intense or mild those emotions are. This can help us better understand the emotional impact of different words and phrases, and how they might be received by different audiences.
By using this two-dimensional emotional space, we can explore how words and phrases can be modified to convey different emotional nuances, and how these modifications might impact the emotional responses of the listener or reader. This can be especially useful in fields such as marketing, advertising, and politics, where the emotional impact of language can be a critical factor in shaping public opinion and behavior.
Later I asked for examples:
Give more examples in this format:
low intensity positive: serene
low intensity neutral: calm
low intensity negative: bored
high intensity positive: excited
high intensity neutral: engaged
high intensity negative: obsessed
And got these nice results:
Sure, here are some more examples in the same format:
I asked ChatGPT
And got the quite good answer:
Later I asked for examples:
And got these nice results: