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(This article was first published on <strong><a href="http://flovv.github.com/AirBnB_demo/"> Florian Teschner</a></strong>, and kindly contributed to <a rel="nofollow" href="http://www.r-bloggers.com/">R-bloggers)</a> </div>
<p>Once in a while I use AirBnB. There are a couple of features that I (intuitively) use to judge if an apartment is save to book; ratings, images of the flat and the user avatar. Apparently, these avatars play an important part in the overall service and usage of AirBnB.<br>
A recent <a target="_blank" href="http://thenextweb.com/insider/2016/04/26/attractive-airbnb-hosts-are-more-likely-to-get-bookings/#gref">study</a> finds that “Attractive Airbnb hosts are more likely to get bookings, even with bad reviews”.</p>
<p>With the easy availability of image recognition services, even the everyday researcher can do a small analysis.<br>
A <a target="_blank" href="http://www.timmteubner.de/">friend</a> provided a small sample of 200 AirBnB avatars which I ran through <a target="_blank" href="http://flovv.github.io/Image-Recognition/">Microsoft’s face recognition API</a>.</p>
<p><img alt="Face detection example" src="http://i2.wp.com/flovv.github.com/figures/imageCollection.png?w=456" data-recalc-dims="1"></p>
<p>Of the 200 images, 117 were labeled as faces, for these faces the API provides a couple of features:<br>
e.g. age, gender, smile detection, mustache detection and the size of the face.</p>
<p>So let’s have a look at the aggregate demographics of our (probably unrepresentative) sample of AirBnB hosts. 62% are male, with an average age of 37.5.<br>
The age distribution is shifted upwards for the male population.</p>
<p><img alt="plot of chunk unnamed-chunk-2" src="http://i2.wp.com/flovv.github.com/figures/post10/unnamed-chunk-2-1.png?w=456" data-recalc-dims="1"></p>
<p>The difference is substantial and significant. Male AirBnB hosts are almost 7 years older than female hosts.</p>
<p><img alt="plot of chunk unnamed-chunk-3" src="http://i1.wp.com/flovv.github.com/figures/post10/unnamed-chunk-3-1.png?w=456" data-recalc-dims="1"></p>
<p>Let’s have a look at the emotion expressed in the avatars. Are female avatars more likely to smile?</p>
<p><img alt="plot of chunk unnamed-chunk-4" src="http://i0.wp.com/flovv.github.com/figures/post10/unnamed-chunk-4-1.png?w=456" data-recalc-dims="1"></p>
<p>Contrary to my base assumption, this is not the case.<br>
Another feature that might be worth exploring is the size of the face rectangle. It is basically a measure of the face to image size ratio.</p>
<p><img alt="plot of chunk unnamed-chunk-5" src="http://i0.wp.com/flovv.github.com/figures/post10/unnamed-chunk-5-1.png?w=456" data-recalc-dims="1"></p>
<p>It seems that guys are more likely to use close-ups as avatars. Even though this study is very limited in the features and sample size used, I can already see the potential of image recognition as an implicit data source to improve e-commerce services.<br>
I wonder if and how AirBnB uses face detection.</p>
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<div>To <strong>leave a comment</strong> for the author, please follow the link and comment on their blog: <strong><a href="http://flovv.github.com/AirBnB_demo/"> Florian Teschner</a></strong>.</div>
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