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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.

Project description

KeyMoji [Emotions in Formula]

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」。

完整介紹

安裝方法

pip3 install KeyMojiAPI

使用方法

KeyMoji Website Demo
KeyMojiAPI Documentation

SENSE2

from KeyMojiAPI import KeyMoji
keymoji = KeyMoji(username="your_username@mail.com", keymojiKey="your_keymoji_key")

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"
}

Visualization

sense2

SENSE8

from KeyMojiAPI import KeyMoji
keymoji = KeyMoji(username="your_username@mail.com", keymojiKey="your_keymoji_key")

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"
}

Visualization

sense8

Tension Visualization

tension

Project details


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