def emotion():
if request.method == "POST":
if "option" not in request.form:
return jsonify(error="must select an option for the NLP function!")
raw, twit = request.form["raw"], False
if request.form["option"] == "twitter":
twit = True
if len(raw) != 0:
ret = nlp.emotion_analysis(raw, twit)
if ret is None:
return jsonift(error="Can't do emotion analysis!")
return jsonify(results=ret)
else:
return render_template("emotion.html")
def emotion():
if request.method == 'POST':
if 'option' not in request.form:
return jsonify(error="must select an option for the NLP function!")
raw, twit = request.form['raw'], False
if request.form['option'] == 'twitter':
twit=True
if len(raw) !=0:
ret = nlp.emotion_analysis(raw,twit)
if ret is None:
return jsonift(error="Can't do emotion analysis!")
return jsonify(results=ret)
else:
return render_template('emotion.html')
def analyze_emotion(filename):
with open(filename, 'rU') as f:
return {filename:dict(nlp.emotion_analysis(f.read()))}
data = pd.read_csv(uploaded_file)
st.write(data)
if st.button('开始挖掘热点'):
'聚类中请稍后...'
df = getHot(data, 0.6, 10)
# Add a placeholder
st.write('聚类完成！')
st.write(df)
if option == '情感倾向分析':
st.title('情感分析系统')
st.markdown('Affective tendency analysis system')
text = st.text_area('请输入要分析的文本')
if st.button('开始分析'):
st.write('分析结果为') #展示一个感情置信度
a, b, c, d = emotion_analysis(text)
chart_data = pd.DataFrame([[c, d]],
columns=['positive_prob', 'negative_prob'])
st.bar_chart(chart_data)
if a == 2:
st.write('正向感情')
st.write('分类置信度为：', b)
elif a == 1:
st.write('中性感情')
st.write('分类置信度为：', b)
else:
st.write('负向感情')
st.write('分类置信度为：', b)
if option == '评论观点抽取':
st.title('观点抽取系统')
