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How do you account for the relative abundance of it in places like Chicago and Philadelphia?
Which map are you looking at? Neither of those cities is particularly well-represented on the "homophobic" or "racist" maps. Zoom in if you don't believe me.
*****, a term used by some homosexuals to define themselves, has a big showing. My wife self identifies as *****.
And it is tracking single words. So a teen tweeting "that's so gay" is counted. It isn't taking into account the context, or who is saying it.
I find it interesting, that when you zoom in it seems small towns are a large percentage of the tweets.
Just look at Atlanta, or New York in the city not much, in the smaller towns surrounding the city big spots.
Which map are you looking at? Neither of those cities is particularly well-represented on the "homophobic" or "racist" maps. Zoom in if you don't believe me.
I clicked on the link and saw a map with most of the eastern United States as being solid red which the key designates as meaning "most hate".
Chicago and Philadelphia are right in the midst of that red block.
*****, a term used by some homosexuals to define themselves, has a big showing. My wife self identifies as *****.
And it is tracking single words. So a teen tweeting "that's so gay" is counted. It isn't taking into account the context, or who is saying it.
Per the researchers, they did actually read the tweets, and were thus able to eliminate some instances where derogatory words were clearly not used in a derogatory manner.
students at Humboldt State manually read and coded the sentiment of each tweet to determine if the given word was used in a positive, negative or neutral manner. This allowed us to avoid using any algorithmic sentiment analysis or natural language processing, as many algorithms would have simply classified a tweet as ‘negative’ when the word was used in a neutral or positive way. For example the phrase ‘d y k e’, while often negative when referring to an individual person, was also used in positive ways (e.g. “d y k e s on bikes #SFPrideâ€). The students were able to discern which were negative, neutral, or positive. Only those tweets used in an explicitly negative way are included in the map.
As for the prevalence of "hate tweets" in certain low-population areas, it's possible that the numbers could have been distorted by a few individual Twits who issue a constant stream of hateful invective.
I clicked on the link and saw a map with most of the eastern United States as being solid red which the key designates as meaning "most hate".
Chicago and Philadelphia are right in the midst of that red block.
Then zoom in. The zoomed-out map blends all of the red blobs together and is not useful. The zoomed-in map reveals exactly where the hateful tweets are coming from. Or are you not interested in knowing that?
Can you zoom in to find the actual homes they live in? I mean after all if somebody tweets something offensive they must be jailed immediately right!!! Gimme a fuggin break. Who cares and why are tax dollars being spent on this nonsense?
Then zoom in. The zoomed-out map blends all of the red blobs together and is not useful. The zoomed-in map reveals exactly where the hateful tweets are coming from. Or are you not interested in knowing that?
If the first thing that one sees when they look at the map is inaccurate information, that calls the entire project into serious question.
If the first thing that one sees when they look at the map is inaccurate information, that calls the entire project into serious question.
It is pretty obvious you have to zoom in... sorry.
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