KeyMoji sentimental analysis system differs from other "amature-tagged" and "pure-ML/DL" text sentimental analysis solutions in many ways. KeyMoji combines "syntactic structure information", "formal semantics" and "lexical semantic model" in one calculating process to estimate the sentimental bias and distributions of sentiments in texts.
KeyMoji 關鍵情緒偵測 (SENSE2、SENSE8、Tension) 採用不同於其它「素人標記」和「純機器學習」的文本情緒偵測分析工具，結合了「句型」、「邏輯語意」和「詞彙模型」，設計出一個完整的「情緒計算過程」。
pip3 install KeyMojiAPI
or
python3 -m pip install KeyMojiAPI
KeyMoji Website Demo
KeyMojiAPI Documentation
from KeyMojiAPI import KeyMoji
# 若您是使用 Docker 版本，無須填入 username, keymoji_key 參數
keymoji = KeyMoji(username="", keymojiKey="")
inputSTR = "他逃離了危險的災難"
result = keymoji.sense2(inputSTR)
print(result)
{
"status": true,
"msg": "Success!",
"results": [
{
"score": 0.2798,
"sentiment": "positive",
"input_str": "他逃離了危險的災難",
"cursing": false
}
],
"sense": "sense2",
"version": "v101"
}
from KeyMojiAPI import KeyMoji
# 若您是使用 Docker 版本，無須填入 username, keymoji_key 參數
keymoji = KeyMoji(username="", keymojiKey="")
inputSTR = "他逃離了危險的災難"
result = keymoji.sense8(inputSTR)
print(result)
{
"status": true,
"msg": "Success!",
"results": [
{
"input_str": "他逃離了危險的災難",
"Joy": 3.7486,
"Trust": 5.1776,
"Surprise": 6.7238,
"Anticipation": 0.9618,
"Fear": 0.9505,
"Sadness": 0.9108,
"Anger": 0.9516,
"Disgust": 0.8876
}
],
"sense": "sense8",
"version": "v101"
}
FAQs
KeyMoji sentimental analysis system differs from other "amature-tagged" and "pure-ML/DL" text sentimental analysis solutions in many ways. KeyMoji combines "syntactic structure information", "formal semantics" and "lexical semantic model" in one calculating process to estimate the sentimental bias and distributions of sentiments in texts.
We found that KeyMojiAPI demonstrated a healthy version release cadence and project activity because the last version was released less than a year ago. It has 1 open source maintainer collaborating on the project.
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