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42
TwitterStand: News in Tweets ∗
"... Twitter is an electronic medium that allows a large user populace to communicate with each other simultaneously. Inherent to Twitter is an asymmetrical relationship between friends and followers that provides an interesting social networklike structure among the users of Twitter. Twitter messages, c ..."
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Cited by 142 (20 self)
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Twitter is an electronic medium that allows a large user populace to communicate with each other simultaneously. Inherent to Twitter is an asymmetrical relationship between friends and followers that provides an interesting social networklike structure among the users of Twitter. Twitter messages, called tweets, are restricted to 140 characters and thus are usually very focused. We investigate the use of Twitter to build a news processing system, called TwitterStand, from Twitter tweets. The idea is to capture tweets that correspond to late breaking news. The result is analogous to a distributed news wire service. The difference is that the identities of the contributors/reporters are not known in advance and there may be many of them. Furthermore, tweets are not sent according to a schedule: they occur as news is happening, and tend to be noisy while usually arriving at a high throughput rate. Some of the issues addressed include removing the noise, determining tweet clusters of interest bearing in mind that the methods must be online, and determining the relevant locations associated with the tweets.
NewsStand: A New View on News
, 2008
"... News articles contain a wealth of implicit geographic content that if exposed to readers improves understanding of today’s news. However, most articles are not explicitly geotagged with their geographic content, and few news aggregation systems expose this content to users. A new system named NewsSt ..."
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Cited by 55 (26 self)
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News articles contain a wealth of implicit geographic content that if exposed to readers improves understanding of today’s news. However, most articles are not explicitly geotagged with their geographic content, and few news aggregation systems expose this content to users. A new system named NewsStand is presented that collects, analyzes, and displays news stories in a map interface, thus leveraging on their implicit geographic content. NewsStand monitors RSS feeds from thousands of online news sources and retrieves articles within minutes of publication. It then extracts geographic content from articles using a custom-built geotagger, and groups articles into story clusters using a fast online clustering algorithm. By panning and zooming in NewsStand’s map interface, users can retrieve stories based on both topical significance and geographic region, and see substantially different stories depending on position and zoom level.
Porting a web-based mapping application to a smartphone app.
- In ACM GIS,
, 2011
"... ABSTRACT NewsStand is a Web-based mapping application that we have developed to enable searching for spatially-referenced information by using a map query interface. Previously, we adapted the Web version to execute on mobile devices such as smartphones where the main issue that was confronted was ..."
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Cited by 13 (11 self)
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ABSTRACT NewsStand is a Web-based mapping application that we have developed to enable searching for spatially-referenced information by using a map query interface. Previously, we adapted the Web version to execute on mobile devices such as smartphones where the main issue that was confronted was how to deal with the considerably smaller display screen while retaining access to the application through the browser. In the current work we discuss the issues that we encountered in converting the Web-based application to a native App primarily on the iPhone and iPod Touch. These issues involve how to compensate for the absence of a hovering action as well as how to integrate an interaction restriction to one hand coupled with use of the thumb as the pointing mechanism. In addition, a significant effort is devoted to the implementation of an intuitive mechanism for undoing the most recent actions. Other issues include the formulation of navigation shortcuts to avoid excessive traffic with the supporting database.
Identification of live news events using Twitter
- In Proceedings of the 3rd ACM SIGSPATIAL International Workshop on LocationBased Social Networks (LBSN '11
, 2011
"... Twitter presents a source of information that cannot easily be obtained anywhere else. However, though many posts on Twitter reveal up-to-the-minute information about events in the world or interesting sentiments, far more posts are of no interest to the general audience. A method to determine which ..."
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Cited by 13 (4 self)
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Twitter presents a source of information that cannot easily be obtained anywhere else. However, though many posts on Twitter reveal up-to-the-minute information about events in the world or interesting sentiments, far more posts are of no interest to the general audience. A method to determine which Twitter users are posting reliable information and which posts are interesting is presented. Using this information a search through a large, online news corpus is conducted to discover future events before they occur along with information about the location of the event. These events can be identified with a high degree of accuracy by verifying that an event found in one news article is found in other similar news articles, since any event interesting to a general audience will likely have more than one news story written about it. Twitter posts near the time of the event can then be identified as interesting if they match the event in terms of keywords or location. This method enables the discovery of interesting posts about current and future events and helps in the identification of reliable users.
Adaptive context features for toponym resolution in streaming news
- In SIGIR’12: Proceedings of the 35th International ACM SIGIR Conference on Research and Development in Information Retrieval
, 2012
"... News sources around the world generate constant streams of information, but effective streaming news retrieval requires an intimate understanding of the geographic content of news. This process of understanding, known as geotagging, consists of first finding words in article text that correspond to ..."
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Cited by 12 (9 self)
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News sources around the world generate constant streams of information, but effective streaming news retrieval requires an intimate understanding of the geographic content of news. This process of understanding, known as geotagging, consists of first finding words in article text that correspond to location names (toponyms), and second, assigning each toponym its correct lat/long values. The latter step, called toponym resolution, can also be considered a classification problem, where each of the possible interpretations for each toponym is classified as correct or incorrect. Hence, techniques from supervised machine learning can be applied to improve accuracy. New classification features to improve toponym resolution, termed adaptive context features, are introduced that consider a window of context around each toponym, and use geographic attributes of toponyms in the window to aid in their correct resolution. Adaptive parameters controlling the window’s breadth and depth afford flexibility in managing a tradeoff between feature computation speed and resolution accuracy, allowing the features to potentially apply to a variety of textual domains. Extensive experiments with three large datasets of streaming news demonstrate the new features ’ effectiveness over two widely-used competing methods. Categories andSubjectDescriptors
TWinner: Understanding news queries with geo-content using Twitter. Paper read at Geographic Information Retrieval, at
, 2010
"... ABSTRACT In the present world scenario, where the search engines wars are becoming fiercer than ever, it becomes necessary for each search engine to realize the intent of the user query to be able to provide him with more relevant search results. Amongst the various categories of search queries, a ..."
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Cited by 6 (0 self)
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ABSTRACT In the present world scenario, where the search engines wars are becoming fiercer than ever, it becomes necessary for each search engine to realize the intent of the user query to be able to provide him with more relevant search results. Amongst the various categories of search queries, a major portion is constituted by those having news intent. Seeing the tremendous growth of social media users, the spatial-temporal nature of the media can prove to be a very useful tool to improve the search quality. In our work we examine the development of such a tool that combines social media in improving the quality of web search and predicting whether the user is looking for news or not. We go one step beyond the previous research by mining Twitter messages, assigning weights to them and determining keywords that can be added to the search query to act as pointers to the existing search engine algorithms suggesting to it that the user is looking for news. We conduct a series of experiments and show the impact that TWinner has on the results.
Supporting Rapid Processing and Interactive Map-Based Exploration of Streaming News ∗
"... The database architecture and system design of NewsStand, a database system that analyzes and displays streaming news using a map user interface, is described. Special emphasis is given to News-Stand’s pipe server, which coordinates individual, independent analysis modules in a processing pipeline, ..."
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Cited by 5 (5 self)
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The database architecture and system design of NewsStand, a database system that analyzes and displays streaming news using a map user interface, is described. Special emphasis is given to News-Stand’s pipe server, which coordinates individual, independent analysis modules in a processing pipeline, and NewsStand’s relational database schema, designed to accommodate responsive spatial querying and retrieval via NewsStand’s user interface. Examples of these spatial queries, which are variants of top-k window queries, are also presented. Experiments on the live NewsStand database system demonstrate its capability for rapidly processing large amounts of streaming news as well as the interactivity of its map user interface as measured by database querying. Categories and Subject Descriptors
Images in News
"... A system, called NewsStand, is introduced that automatically extracts images from news articles. The system takes RSS feeds of news article and applies an online clustering algorithm so that articles belonging to the same news topic can be associated with the same cluster. Using the feature vector a ..."
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A system, called NewsStand, is introduced that automatically extracts images from news articles. The system takes RSS feeds of news article and applies an online clustering algorithm so that articles belonging to the same news topic can be associated with the same cluster. Using the feature vector associated with the cluster, the images from news articles that form the cluster are extracted. First, the caption text associated with each of the images embedded in the news article is determined. This is done by analyzing the structure of the news article’s HTML page. If the caption and feature vector of the cluster are found to contain keywords in common, then the image is added to an image repository. Additional meta-information are now associated with each image such as caption, cluster features, names of people in the news article, etc. A very large repository containing more than 983k images from 12 million news articles was built using this approach. This repository also contained more than 86.8 million keywords associated with the images. The key contribution of this work is that it combines clustering and natural language processing tasks to automatically create a large corpus of news images with good quality tags or meta-information so that interesting vision tasks can be performed on it. Keywords-News images; online clustering; image tags, news image corpus
Augmenting spatio-textual search with an infectious disease ontology
- In IIMAS’08: Proceedings of the Workshop on Information Integration Methods, Architectures, and Systems
, 2008
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A Case Study of Using Geographic Cues to Predict Query News Intent
"... Geographic information retrieval encompasses important tasks including finding the location of a user, and locations relevant to their search queries. Web-based search engines receive queries from numerous users located in very different parts of the world. A typical way for people to find news is t ..."
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Cited by 4 (1 self)
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Geographic information retrieval encompasses important tasks including finding the location of a user, and locations relevant to their search queries. Web-based search engines receive queries from numerous users located in very different parts of the world. A typical way for people to find news is through a general web search engine, which makes it important for search engines to recognize queries with news intent. An important question for geographic information retrieval is how we can benefit from geographic cues to predict the intent of users. This work presents a case study of an application using geographic features to improve the quality of an important web search task, involving predicting which queries have news intent and hence are likely to receive clicks on news search results. Our case study suggests that information derived from geographic features can help the task. The information we consider includes cues derived from the location of the user, from the IP address, the location relevant to the query, automatically extracted from the query string, and the relation between the two locations. We build a classifier that uses geographical cues to predict whether a query will result in a news click or not. We compare our classifier to a strong baseline that use non-geographic clickbased features and we show that our classifier outperforms the baseline for geographic queries.
