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| Content Provider | ACM Digital Library |
|---|---|
| Author | Rokicki, Markus Herder, Eelco Trattner, Christoph Kuśmierczyk, Tomasz |
| Abstract | Historically, there have always been differences in how men and women cook or eat. The reasons for this gender divide have mostly gone in Western culture, but still there is qualitative and anecdotal evidence that men prefer heftier food, that women take care of everyday cooking, and that men cook to impress. In this paper, we show that these differences can also quantitatively be observed in a large dataset of almost 200 thousand members of an online recipe community. Further, we show that, using a set of 88 features, the gender of the cooks can be predicted with fairly good accuracy of 75%, with preference for particular dishes, the use of spices and the use of kitchen utensils being the strongest predictors. Finally, we show the positive impact of our results on online food recipe recommender systems that take gender information into account. |
| Starting Page | 207 |
| Ending Page | 215 |
| Page Count | 9 |
| File Format | |
| ISBN | 9781450343688 |
| DOI | 10.1145/2930238.2930248 |
| Language | English |
| Publisher | Association for Computing Machinery (ACM) |
| Publisher Date | 2016-07-13 |
| Publisher Place | New York |
| Access Restriction | Subscribed |
| Subject Keyword | Cooking Classification Gender differences Online food Food recommender systems |
| Content Type | Text |
| Resource Type | Article |
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