<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>yid</author><text>&amp;gt; Holy shit.. can you imagine someone just plotting all the trips from a single gay bar? Listing off all the connected residential addresses? And not only that, any subsequent trips home from those addresses the next morning? Taking the walk of shame to a whole new level!&lt;p&gt;There are some weird assumptions going on here, in addition to the fact that you grossly overestimate the precision to which GPS data can de-anonymize individuals who are using a shared, public transport mechanism in a city as densely crowded as NYC. The density of people and businesses alone makes individual identification difficult, not to mention weak GPS signals and low accuracy with skyscrapers every hundred yards. Is there any evidence that the logs have enough accuracy to do what you&amp;#x27;re claiming, or are you just wildly speculating?</text><parent_chain><item><author>abalone</author><text>Whoa, whoa.... You&amp;#x27;re telling me there&amp;#x27;s a public data set of &lt;i&gt;all taxi trip geolocation data with GPS precision&lt;/i&gt;? That&amp;#x27;s f&amp;#x27;ing insane!&lt;p&gt;I think there&amp;#x27;s a MUCH bigger privacy issue here than what the author focuses on.&lt;p&gt;Couldn&amp;#x27;t you deduce many &lt;i&gt;passenger&lt;/i&gt; identities based on addresses? There&amp;#x27;s a lot of scenarios where passenger identities could be effectively de-anonymized, just based on GPS data. You could then use this data set to analyze their comings and goings.&lt;p&gt;1. For people who live alone in a single family home, you can pretty much completely track when and where they went by taxi. From this you can deduce a lot about their interests, lifestyle, workplace and schedule, private life, etc. It&amp;#x27;s profoundly invasive.&lt;p&gt;2. Even if there&amp;#x27;s a few people sharing an address, the other dropoff&amp;#x2F;pickup point can be used to narrow down the likelihood of who it is, especially when combined with other easily obtainable data.&lt;p&gt;For example if you knew an employee (e.g. that cute barista) lived in a certain neighborhood you could track their trips to&amp;#x2F;from work and deduce their home address.&lt;p&gt;Or if you knew there was only one senior citizen (or Muslim, etc.) living in a building, a regular trip to a senior center (or mosque) would reveal when their apartment is vacant.&lt;p&gt;Or if there&amp;#x27;s only one young man in a building, a single trip home from a gay bar could out them.&lt;p&gt;Holy shit.. can you imagine someone just plotting all the trips from a single gay bar? Listing off all the connected residential addresses? And not only that, &lt;i&gt;any subsequent trips home from those addresses the next morning&lt;/i&gt;? Taking the walk of shame to a whole new level!&lt;p&gt;Likewise trips could be used to deduce affairs and other deceptions by fellow residents. &amp;quot;You said you were working late, but the only taxi trip to our building that night was from a bar.&amp;quot;&lt;p&gt;This is just off the top of my head.. I feel I could go on for hours listing all the possible ways this data set could be exploited.&lt;p&gt;How is this not front page New York Times???</text></item></parent_chain></comment><story><title>Lessons from NYC’s improperly anonymized taxi logs</title><url>https://medium.com/@vijayp/of-taxis-and-rainbows-f6bc289679a1</url></story>
<instructions>Your goal is to analyze the following comment and estimate how highly it will be upvoted by the Hacker News community.</instructions><comment><author>Hominem</author><text>I think the way cabs actually operate in NYC makes this practically impossible unless you already have some details such as the lat&amp;#x2F;Lon of dropoff and pickup and time of the stops.&lt;p&gt;I&amp;#x27;m assuming the data is for yellow cabs and the new lime green &amp;quot;boro cabs&amp;quot; you hail on the street, not &amp;quot;car service&amp;quot; cars where you schedule a pickup and dropoff to specific addresses.&lt;p&gt;Most bars in Manhattan are storefronts in 3-4 story residential buildings. There are apartments above and they are surrounded by other buildings with apartments and businesses. I don&amp;#x27;t think you could identify a bar. Now strip clubs on the other hand are required by law to be tucked away in isolated locations. Might be possible to identify a strip club.&lt;p&gt;When you hail a cab, and many times when you get dropped off, it happens on a corner, perhaps over a block away, where it is easier to find a free cab.&lt;p&gt;Most cabs are in Manhattan, not a lot of single family homes. Single family homes in the outer boroughs will have almost no yellow cab coverage for pickup and finding a cab that will take you out of Manhattan can be dicey, although I guess those lime green cabs are meant to address that. SI, the Bronx and huge swaths of Brooklyn and Queens pickups will be almost non existant, people going from the outer boroughs will most likely use a car service.&lt;p&gt;I will certainly be checking to see if I can identify any of my rides.</text><parent_chain><item><author>abalone</author><text>Whoa, whoa.... You&amp;#x27;re telling me there&amp;#x27;s a public data set of &lt;i&gt;all taxi trip geolocation data with GPS precision&lt;/i&gt;? That&amp;#x27;s f&amp;#x27;ing insane!&lt;p&gt;I think there&amp;#x27;s a MUCH bigger privacy issue here than what the author focuses on.&lt;p&gt;Couldn&amp;#x27;t you deduce many &lt;i&gt;passenger&lt;/i&gt; identities based on addresses? There&amp;#x27;s a lot of scenarios where passenger identities could be effectively de-anonymized, just based on GPS data. You could then use this data set to analyze their comings and goings.&lt;p&gt;1. For people who live alone in a single family home, you can pretty much completely track when and where they went by taxi. From this you can deduce a lot about their interests, lifestyle, workplace and schedule, private life, etc. It&amp;#x27;s profoundly invasive.&lt;p&gt;2. Even if there&amp;#x27;s a few people sharing an address, the other dropoff&amp;#x2F;pickup point can be used to narrow down the likelihood of who it is, especially when combined with other easily obtainable data.&lt;p&gt;For example if you knew an employee (e.g. that cute barista) lived in a certain neighborhood you could track their trips to&amp;#x2F;from work and deduce their home address.&lt;p&gt;Or if you knew there was only one senior citizen (or Muslim, etc.) living in a building, a regular trip to a senior center (or mosque) would reveal when their apartment is vacant.&lt;p&gt;Or if there&amp;#x27;s only one young man in a building, a single trip home from a gay bar could out them.&lt;p&gt;Holy shit.. can you imagine someone just plotting all the trips from a single gay bar? Listing off all the connected residential addresses? And not only that, &lt;i&gt;any subsequent trips home from those addresses the next morning&lt;/i&gt;? Taking the walk of shame to a whole new level!&lt;p&gt;Likewise trips could be used to deduce affairs and other deceptions by fellow residents. &amp;quot;You said you were working late, but the only taxi trip to our building that night was from a bar.&amp;quot;&lt;p&gt;This is just off the top of my head.. I feel I could go on for hours listing all the possible ways this data set could be exploited.&lt;p&gt;How is this not front page New York Times???</text></item></parent_chain></comment><story><title>Lessons from NYC’s improperly anonymized taxi logs</title><url>https://medium.com/@vijayp/of-taxis-and-rainbows-f6bc289679a1</url></story>