Airbnb主机配置文件的自动分析。
AirProfile的Python项目详细描述
用于自动分析Airbnb主机配置文件的Python包。
该软件包采用Airbnb个人资料，自动标记每个句子的主题，并预测与其他长度相似的个人资料相比，该个人资料是否更值得信赖。
示例用法
LIWC2007是预测信任所需的专有依赖项。不幸的是，由于法律原因，我们不能将其包含在这个包中。
但是，如果您没有LIWC，您仍然可以执行主题分类。
fromAirProfileimportAirProfileap=AirProfile(liwc_path='../LIWC2007/liwc_2007.trie')# or ap = AirProfile() if you do not have LIWC.# Example Airbnb host profile.input="""I have spent my life in the service industry. I look forward to being your host and I look forward to meeting you."""# Segments the input at the sentence level and returns the probability that# each sentence is tagged with the topics described in [1]. This works with or# without LIWC.ap.predict_topics(input)>>>[['i have spent my life in the service industry',{'relationships':0.02,'workEducation':0.99,'travel':0.0,'originResidence':0.07,'lifeMottoValues':0.03,'hospitality':0.02,'interestsTastes':0.03,'personality':0.02}],['i look forward to being your host and i look forward to meeting you',{'relationships':0.0,'workEducation':0.0,'travel':0.02,'originResidence':0.0,'lifeMottoValues':0.0,'hospitality':1.0,'interestsTastes':0.0,'personality':0.04}]]# Segments the input at the sentence level and returns the probability that# the profile is perceived to be more trustworthy compared to other profiles# of similar length. This requires LIWC and will throw an error otherwise.ap.predict_trust(input)>>>Prediction(prob=0.49,predict=0)
参考文献
[1]Airbnb主机配置文件的自我披露和可信赖性。小马，杰夫·汉考克，肯尼斯·林明杰，还有莫尔·纳曼。CSCW 2017年。最佳论文荣誉奖。[PDF1]
[2]Airbnb主机配置文件可信任度的计算方法。小马，特里莎拉·尼拉吉，莫·纳曼。ICWSM 2017。海报。[PDF2]
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