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Authorship Attribution in Greek Tweets Using Author's Multilevel N-Gram Profiles

AAAI Conferences

The aim of this study is to explore authorship attribution methods in Greek tweets. We have developed the first Modern Greek Twitter corpus (GTC) consisted of 12,973 tweets crawled from 10 Greek popular users. We used this corpus in order to study the effectiveness of a specific document representation called Author's Multilevel N-gram Profile (AMNP) and the impact of different methods on training data construction for the task of authorship attribution. In order to address the above research questions we used GTC to create 4 different datasets which contained merged tweets in texts of different sizes (100, 75, 50 and 25 words). Results were evaluated using authorship attribution accuracy both in 10-fold cross-validation and in an external test set compiled from actual tweets. AMNP representation achieved significant better accuracies than single feature groups across all text sizes.


Is AI following gender stereotypes? Relocate Guest Author Relocate magazine

#artificialintelligence

Robots, AI and technology - what does it mean for our collective future that technology is increasingly human-like and gendered? And, what does it tell us about our capacity to create a very human future? This publication (or any part thereof) may not be reproduced in any form without the prior written permission of Profile Locations. Profile Locations accepts no liability for the accuracy of the contents or any opinions expressed herein.


[R] Would you like to co-author a time series data mining paper with Dr. Eamonn Keogh's Lab? • r/MachineLearning

@machinelearnbot

Would you like to co-author a paper with Dr. Eamonn Keogh's Lab? The paper, to be submitted to the Data Mining Journal [a] in late Summer or early Fall, is likely to be one of the top ten most cited paper in the journal [b]. Obviously, we cannot guarantee that paper will be accepted, but with 20 papers in the journal, Dr. Keogh is currently the most prolific author in the Data Mining Journal, and will submit a very strong paper. In brief, the proposed paper claims that, given a data structure called the Matrix Profile, you can often add just 5 to 10 lines of code, to solve an interesting problem. We plan to find about seven more such ideas.


Dying author pens heartbreaking dating profile for her beloved husband

Mashable

We've all read a lot of online dating profiles in our time, but you've probably never read one as heartbreakingly good as this one. Amy Krouse Rosenthal, who is terminally ill with ovarian cancer, penned a stunning essay for this week's Modern Love in the New York Times in which she glowingly recommends her husband, Jason, and urges someone to swipe right on him. It's as beautifully written as it is soul-crushingly sad. Perhaps that's not surprising, since Rosenthal is the bestselling author of many classic children's books -- Little Pea, Spoon, and Duck! From her deathbed, she lovingly details many of Jason's wonderful qualities ("he can flip a pancake"), and in the process paints a picture of their happy courtship and 26 years together.


Finding Influential Authors in Brand-Page Communities

AAAI Conferences

Enterprises are increasingly using social media forums to engage with their customer online- a phenomenon known as Social Customer Relation Management (Social CRM) . In this context, it is important for an enterprise to identify “influential authors” and engage with them on a priority basis. We present a study towards finding influential authors on Twitter forums where an implicit network based on user interactions is created and analyzed. Furthermore, author profile features and user interaction features are combined in a decision tree classification model for finding influential authors. A novel objective evaluation criterion is used for evaluating various features and modeling techniques. We compare our methods with other approaches that use either only the formal connections or only the author profile features and show a significant improvement in the classification accuracy over these baselines as well as over using Klout score.