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Collaborating Authors

Here are the 13 best tweets of the week

Mashable

Here we are: Another week of quarantine, another week of Good Tweets. We've been keeping tracking of the best tweets for six weeks now. Because life in isolation is boring and stressful and sometimes it's good to laugh at dumb posts on the internet. OK, enough throat clearing, here they are: the 13 Good Tweets. Been distance-teaching Romeo and Juliet to my freshmen and one of them sent me this meme today and I have never been more fulfilled in this job#TeacherLife pic.twitter.com/RDgeGpERhc


The best tweets of 2018 so far

Mashable

It may seem impossible that, in our current cursed reality, anyone could generate even a single good tweet. For the most part, this is true. But there are a few tweets that rise above. These are the good tweets, the tweets that perhaps -- against all odds -- even made us laugh. Does anyone remember what laughing feels like?


The best tweets of the week, including Garth Maul and Corn Palace

Mashable

We did it folks, it's Friday. Anyways, do you like good tweets because we've got good tweets. We've been collecting the best posts of the week for a while now because we can and what else do you have to do in quarantine but read tweets? Well, alright then, let's do this. Here are 16 of our favorite tweets from this week.


Premier League player could be punished for homophobic tweets from 2012

Mashable

Burnley striker Andre Gray is facing possible discipline by the English Football Association for homophobic tweets he made four years ago -- even though they were made before the FA instituted the rule that's being used to punish him. Gray scored his first Premier League goal in Burnley's 2-0 win over Liverpool on Saturday. After the goal, fans began to re-share some of Gray's old tweets in which he had made homophobic comments. Gray has since deleted the tweets but screenshots are still making the rounds. Additional offensive tweets were also brought to light.


Weber

AAAI Conferences

We present a system that visualizes geo-temporal Twitter activity. The distinguishing features our system offers include, (i) a large degree of user freedom in specifying the subset of data to visualize and (ii) a focus on *discriminative* patterns rather than high volume patterns. Tweets with precise GPS co-ordinates are assigned to geographical cells and grouped by (i) tweet language, (ii) tweet topic, (iii) day of week, and (iv) time of day. The spatial resolutions of the cells is determined in a data-driven manner using quad-trees and recursive splitting. The user can then choose to see data for, say, English tweets on weekend evenings for the topic "party". This system has been implemented for 1.8 million geo-tagged tweets from Qatar (http://qtr.qcri.org/)