SIGGRAPH '85 Proceedings of the 12th annual conference on Computer graphics and interactive techniques
A quadtree medial axis transform
Communications of the ACM
Use of the SAND spatial browser for digital government applications
Communications of the ACM
Benchmarking Spatial Join Operations with Spatial Output
VLDB '95 Proceedings of the 21th International Conference on Very Large Data Bases
Speeding up construction of PMR quadtree-based spatial indexes
The VLDB Journal — The International Journal on Very Large Data Bases
Web-a-where: geotagging web content
Proceedings of the 27th annual international ACM SIGIR conference on Research and development in information retrieval
Efficient query processing on spatial networks
Proceedings of the 13th annual ACM international workshop on Geographic information systems
K-Nearest Neighbor Finding Using MaxNearestDist
IEEE Transactions on Pattern Analysis and Machine Intelligence
Proceedings of the 16th ACM SIGSPATIAL international conference on Advances in geographic information systems
Meme-tracking and the dynamics of the news cycle
Proceedings of the 15th ACM SIGKDD international conference on Knowledge discovery and data mining
Proceedings of the 17th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Geotagging: using proximity, sibling, and prominence clues to understand comma groups
Proceedings of the 6th Workshop on Geographic Information Retrieval
Short and tweet: experiments on recommending content from information streams
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Recommending twitter users to follow using content and collaborative filtering approaches
Proceedings of the fourth ACM conference on Recommender systems
Determining the spatial reader scopes of news sources using local lexicons
Proceedings of the 18th SIGSPATIAL International Conference on Advances in Geographic Information Systems
Everyone's an influencer: quantifying influence on twitter
Proceedings of the fourth ACM international conference on Web search and data mining
Adapting a map query interface for a gesturing touch screen interface
Proceedings of the 20th international conference companion on World wide web
HCI for peace: a call for constructive action
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
Multifaceted toponym recognition for streaming news
Proceedings of the 34th international ACM SIGIR conference on Research and development in Information Retrieval
The Filter Bubble: What the Internet Is Hiding from You
The Filter Bubble: What the Internet Is Hiding from You
Identification of live news events using Twitter
Proceedings of the 3rd ACM SIGSPATIAL International Workshop on Location-Based Social Networks
Porting a web-based mapping application to a smartphone app
Proceedings of the 19th ACM SIGSPATIAL International Conference on Advances in Geographic Information Systems
Identifying influential users by their postings in social networks
Proceedings of the 3rd international workshop on Modeling social media
Adaptive context features for toponym resolution in streaming news
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Twanchor text: a preliminary study of the value of tweets as anchor text
SIGIR '12 Proceedings of the 35th international ACM SIGIR conference on Research and development in information retrieval
Supporting rapid processing and interactive map-based exploration of streaming news
Proceedings of the 20th International Conference on Advances in Geographic Information Systems
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TwitterStand is a novel way to track the news cycle by allowing people to view and browse the news with a map query interface. TF-IDF scores for each document that is linked to by a tweet (also termed twanchor [22] when the document is a news article) are calculated after they enter the system and pass initial classification filters. These scores are used to cluster similar tweets. Clusters must contain tweets from reputable sources in order for the clusters to form. These reputable sources are known as seeders as they essentially seed a cluster. Seeders have become an integral part of the TwitterStand architecture. An optimal system monitors the set of seeders in order to find newsworthy tweets quickly. This paper proposes methods to improve the current list of seeders by augmenting the pool with previously undiscovered users while routinely eliminating those that do not bring any value. We consider a successful seeder one who is timely in the reporting of large newsworthy events. An analysis of the current seeders precedes a proposed approach and serves as the basis for quantifying future seeder churn. A qualitative analysis based on that approach is conducted in an effort to quantitatively evaluate the process.