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Text-Based Twitter User Geolocation Prediction

by Bo Han, Paul Cook
"... Geographical location is vital to geospatial applications like local search and event detection. In this paper, we investigate and improve on the task of text-based geolocation prediction of Twitter users. Previous studies on this topic have typically assumed that geographical references (e.g., gaze ..."
Abstract - Cited by 9 (0 self) - Add to MetaCart
Geographical location is vital to geospatial applications like local search and event detection. In this paper, we investigate and improve on the task of text-based geolocation prediction of Twitter users. Previous studies on this topic have typically assumed that geographical references (e

Understanding experts’ and novices’ expertise judgment of twitter users

by Q. Vera Liao, Claudia Wagner, Peter Pirolli, Wai-tat Fu - In CHI , 2012
"... Judging topical expertise of micro-blogger is one of the key challenges for information seekers when deciding which information sources to follow. However, it is unclear how useful different types of information are for people to make expertise judgments and to what extent their background knowledge ..."
Abstract - Cited by 7 (0 self) - Add to MetaCart
knowledge influences their judgments. This study explored differences between experts and novices in inferring expertise of Twitter users. In three conditions, participants rated the level of expertise of users after seeing (1) only the tweets, (2) only the contextual information including short

A.: Interest classification of Twitter users using Wikipedia

by Kwan Hui Lim, Amitava Datta - In: WikiSym+OpenSym ’13: Proceedings of the 9th International Symposium on Wikis and Open Collaboration. (Aug 2013
"... We present a framework for (automatically) classifying the relative interests of Twitter users using information from Wikipedia. Our proposed framework first uses Wikipedia to automatically classify a user’s celebrity followings into various interest categories, followed by determining the relative ..."
Abstract - Cited by 2 (1 self) - Add to MetaCart
We present a framework for (automatically) classifying the relative interests of Twitter users using information from Wikipedia. Our proposed framework first uses Wikipedia to automatically classify a user’s celebrity followings into various interest categories, followed by determining the relative

TRank: ranking Twitter users according to specific topics

by Manuela Montangero , Marco Furini
"... Abstract-Twitter is the most popular real-time microblogging service and it is a platform where users provide and obtain information at rapid pace. In this scenario, one of the biggest challenge is to find a way to automatically identify the most influential users of a given topic. Currently, there ..."
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Abstract-Twitter is the most popular real-time microblogging service and it is a platform where users provide and obtain information at rapid pace. In this scenario, one of the biggest challenge is to find a way to automatically identify the most influential users of a given topic. Currently

Inferring latent attributes of Twitter users with label regularization

by Ehsan Mohammady Ardehaly, Aron Culotta
"... Inferring latent attributes of online users has many applications in public health, politics, and marketing. Most existing approaches rely on supervised learning algorithms, which re-quire manual data annotation and therefore are costly to develop and adapt over time. In this paper, we propose a lig ..."
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lightly supervised approach based on label regularization to in-fer the age, ethnicity, and political orientation of Twitter users. Our approach learns from a heterogeneous collection of soft constraints derived from Census demographics, trends in baby names, and Twitter accounts that are em

What is Twitter, a Social Network or a News Media?

by Haewoon Kwak, Changhyun Lee, Hosung Park, Sue Moon
"... Twitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets. The goal of this paper is to study the topological charac ..."
Abstract - Cited by 991 (12 self) - Add to MetaCart
Twitter, a microblogging service less than three years old, commands more than 41 million users as of July 2009 and is growing fast. Twitter users tweet about any topic within the 140-character limit and follow others to receive their tweets. The goal of this paper is to study the topological

Recommending twitter users to follow using content and collaborative filtering approaches

by John Hannon, Mike Bennett, Barry Smyth - In RecSys 2010
"... Recently the world of the web has become more social and more real-time. Facebook and Twitter are perhaps the exemplars of a new generation of social, real-time web services and we believe these types of service provide a fertile ground for recommender systems research. In this paper we focus on one ..."
Abstract - Cited by 81 (7 self) - Add to MetaCart
to harness the real-time web as the basis for profiling and recommendation. To this end we evaluate a range of different profiling and recommendation strategies, based on a large dataset of Twitter users and their tweets, to demonstrate the potential for effective and efficient followee recommendation.

Why We Twitter: Understanding Microblogging Usage and Communities

by Akshay Java, Tim Finin
"... Microblogging is a new form of communication in which users can describe their current status in short posts distributed by instant messages, mobile phones, email or the Web. Twitter, a popular microblogging tool has seen a lot of growth since it launched in October, 2006. In this paper, we present ..."
Abstract - Cited by 576 (2 self) - Add to MetaCart
Microblogging is a new form of communication in which users can describe their current status in short posts distributed by instant messages, mobile phones, email or the Web. Twitter, a popular microblogging tool has seen a lot of growth since it launched in October, 2006. In this paper, we present

The Tweets They are a-Changin’: Evolution of Twitter Users and Behavior

by Yabing Liu, Chloe Kliman-silver, Alan Mislove
"... The microblogging site Twitter is now one of the most popular Web destinations. Due to the relative ease of data access, there has been significant research based on Twitter data, ranging from measuring the spread of ideas through society to predicting the behavior of real-world phenomena such as th ..."
Abstract - Cited by 12 (0 self) - Add to MetaCart
its founding, and it remains unclear whether prior results still hold, and whether the (often implicit) as-sumptions of proposed systems are still valid. In this paper, we take a first step towards answering these question by focusing on the evolution of Twit-ter’s users and their behavior. Using a

Gender Inference of Twitter Users in Non-English Contexts

by Morgane Ciot, Morgan Sonderegger, Derek Ruths
"... While much work has considered the problem of latent attribute inference for users of social media such as Twitter, little has been done on non-English-based content and users. Here, we conduct the first assessment of latent at-tribute inference in languages beyond English, focusing on gender infere ..."
Abstract - Cited by 9 (0 self) - Add to MetaCart
While much work has considered the problem of latent attribute inference for users of social media such as Twitter, little has been done on non-English-based content and users. Here, we conduct the first assessment of latent at-tribute inference in languages beyond English, focusing on gender
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Results 11 - 20 of 1,973
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