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Abdullah Almaatouq

Researcher at Massachusetts Institute of Technology

Publications -  18
Citations -  475

Abdullah Almaatouq is an academic researcher from Massachusetts Institute of Technology. The author has contributed to research in topics: Social influence & Unemployment. The author has an hindex of 8, co-authored 16 publications receiving 331 citations. Previous affiliations of Abdullah Almaatouq include King Abdulaziz City for Science and Technology.

Papers
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Journal ArticleDOI

Measuring the predictability of life outcomes with a scientific mass collaboration.

Matthew J. Salganik, +114 more
TL;DR: Practical limits to the predictability of life outcomes in some settings are suggested and the value of mass collaborations in the social sciences is illustrated.
Journal ArticleDOI

Adaptive social networks promote the wisdom of crowds

TL;DR: The results reveal that, in the presence of plasticity and feedback, social networks can adapt to biased and changing information environments and produce collective estimates that are more accurate than their best-performing member.
Journal ArticleDOI

If it looks like a spammer and behaves like a spammer, it must be a spammer: analysis and detection of microblogging spam accounts

TL;DR: It is shown that there exist two behaviorally distinct categories of spammers and that they employ different spamming strategies, and the detectability of spam accounts with respect to three categories of features, namely content attributes, social interactions, and profile properties.
Journal ArticleDOI

Are You Your Friends’ Friend? Poor Perception of Friendship Ties Limits the Ability to Promote Behavioral Change

TL;DR: It is found that people are typically poor at perceiving the directionality of their friendship ties and that this can significantly limit their ability to engage in cooperative arrangements, and strategies to overcome this limitation are suggested.
Proceedings ArticleDOI

Twitter: who gets caught? observed trends in social micro-blogging spam

TL;DR: It is shown that there exist two behaviorally distinct categories of twitter spammers and that they employ different spamming strategies, and the users in these two categories demonstrate different individual properties as well as social interaction patterns.