Jianwei Zhang

A Novel Visualization Method for Distinction of Web News Sentiment

Recently, an increasing number of news websites have come to provide various featured services. However, effective analysis and presentation for distinction of viewpoints among different news sources are limited. We focus on the sentiment aspect of news reporters viewpoints and propose a system called the Sentiment Map for distinguishing the sentiment of news articles and visualizing it on a geographical map based on map zoom control. The proposed system provides more detailed sentiments than conventional sentiment analysis which only considers positive and negative emotions. When a user enters one or more query keywords, the sentiment map not only retrieves news articles related to the concerned topic, but also summarizes sentiment tendencies of Web news based on specific geographical scales. Sentiments can be automatically aggregated at different levels corresponding to the change of map scales. Furthermore, we take into account the aspect of time, and show the variation in sentiment over time. Experimental evaluations conducted by a total of 100 individuals show the sentiment extraction accuracy and the visualization effect of the proposed system are good.

A Tourist Route Search System Based on Web Information and the Visibility of Scenic Sights

With the growth of massive information on the Web, information recommendation and filtering techniques have been studied intensively.Traditional route search systems, which can be considered one of information recommendation systems, usually calculate the shortest path in terms of time or distance.Recently, route search systems for more general purposes have become an important research topic.In this paper we propose an efficient tourist route search system which not only recommends the path simply connecting several tourist spots, but also recommends the path with beautiful scenic sights.We focus on the visibility of scenic sights between one tourist spot and another, which is an important factor for choosing a driving route, but has not been considered in traditional tourist navigation systems.To automatically retrieve tourist spots, we propose a personalized tourist spot recommendation technique using the Web information.To find a route with attractive scenery, scores for paths based on the visibility of scenic sights are calculated and utilized.We tested the effectiveness of the proposed system by using a prototype of the system.

Tour recommendation system based on web information and GIS

Information recommendation and filtering techniques have been studied intensively. Traditional tour recommendation systems, which can be considered one of information recommendation systems, usually calculate the shortest path in terms of time or distance. Recently, tour recommendation systems for more general purposes have become an important research topic. In this paper we propose an efficient tourist route search system which not only recommends the path simply connecting several tourist spots, but also recommends the path with beautiful scenic sights. We focus on the visibility of scenic sights between one tourist spot and another, which is an important factor for choosing a driving route, but has not been considered in traditional tour recommendation systems. To automatically retrieve tourist spots, we propose a personalized tourist spot recommendation technique using the Web information. Although, for some regions, databases of the famous spots exist and are published, such regions are limited and usually outdated. Our method automatically extracts spots from the Web, thus our system is versatile and up-to-date for large regions. To find a route with attractive scenery, we calculate scores for paths based on the visibility of scenic sights. After generating route candidates using GIS, a 3D virtual space is constructed and the Z-Buffer method is used to decide the visibility of scenic sights for each route candidate. We implemented a prototype and tested the effectiveness of the system.

Blog Ranking Based on Bloggers' Knowledge Level for Providing Credible Information

With the huge increase of recently popular user-generated content on the Web, searching for credible information has become progressively difficult. In this paper, we focus on blogs, one kind of user-generated content, and propose a credibility-focused blog ranking method based on bloggers knowledge level. This method calculates knowledge scores for bloggers and ranks blog entries based on bloggers knowledge level. Bloggers knowledge level is evaluated based on their usage of domain-specific words in their past blog entries. A blogger is given multiple scores with respect to various topic areas. In our method, blog entries written by knowledgeable bloggers have higher rankings than those written by common bloggers. Additionally, our system can present multiple ranking lists of blog entries from the perspectives of different bloggers groups. This allows users to estimate the trustworthiness of blog contents from multiple aspects. We built a prototype of the proposed system, and our experimental evaluation showed that our method could effectively rank bloggers and blog entries.

Early detection of buzzwords based on large-scale time-series analysis of blog entries

In this paper, we discuss a method for early detection of gradual buzzwords by analyzing time-series data of blog entries. We observe the process in which certain topics grow to become major buzzwords and determine the key indicators that are necessary for their early detection. From the analysis results based on 81,922,977 blog entries from 3,776,154 blog websites posted in the past two years, we find that as topics grow to become major buzzwords, the percentages of blog entries from the blogger communities closely related to the target buzzword decrease gradually, and the percentages of blog entries from the weakly related blogger communities increase gradually. We then describe a method for early detection of these buzzwords, which is dependent on identifying the blogger communities which are closely related to these buzzwords. Moreover, we verify the effectiveness of the proposed method through experimentation that compares the rankings of several buzzword candidates with a real-life idol group popularity competition.

Sentiment Bias Detection in Support of News Credibility Judgment

Recently, an increasing number of online news websites have come to provide news browsing and retrieval services. For certain topics, certain news websites may hold sentiment bias, and therefore select and edit information according to their own standpoints before delivering news articles. Lacking conscious awareness of websites sentiment bias may result in blind obedience to the reported information. We focus on the sentiment aspect of news articles and develop a system which can detect and visualize sentiment tendencies of different websites. Given a topic, the system extracts relevant subtopics and presents sentiment difference between different subtopics. Once a subtopic is specified, sentiment difference between news websites is also provided. The background knowledge of sentiment difference between subtopics and between websites can assist users in judging the news credibility. In particular, the system analyzes four-dimension sentiment, which is more similar to human emotion than conventional positive-negative sentiment. Experimental evaluations show the accuracy of sentiment extraction and subtopic extraction is good, and our observation results show sentiment bias can be detected by the system.

Diverse sentiment comparison of news websites over time

Conventional pos-neg model of sentiment analysis primarily for review documents is inappropriate for news articles because of the sentiment diversity of the latter. We design three-dimension sentiments that are more suitable for the analysis of news articles. For a contentious topic, different news websites may have different sentiment tendencies and the tendencies may vary over time. To catch this feature, we construct a sentiment dictionary and develop a system that can extract news articles sentiments, present sentiment variation over time inside a news website, and compare sentiment correlation between news websites.

Evaluating credibility of web information

We describe a new concept and method for evaluating the Web information credibility. The quality control of information (text, image, video etc.) on the Web is generally insufficient due to low publishing barriers. As a result, there is a large amount of mistaken and unreliable information on the Web that can have detrimental effects on users. This calls for technology that facilitates the judging of the credibility (expertise and trustworthiness) of Web content and the accuracy of the information that users encounter on the Web. Such technology should be able to handle a wide range of tasks: extracting several credibility-related features from the target Web content, extracting reputation-related information for the target Web content, such as hyperlinks and social bookmarks and evaluating its distribution, and evaluating features of the target content authors. We propose and describe methodologies of analyzing information credibility of Web information: (1) content analysis, (2) social support analysis and (3) author analysis. We overview our recent research activities on Web information credibility evaluation based on this methodologies.

Page as a Meeting Place: Web Search Augmented with Social Communication

When searching for information, a user generally uses search engines on the web. Often search results do not satisfy all users because they may have different needs and varying levels of knowledge. We develop a search system that combines the merits of searching and social communication for improving user experience on the web. This system includes a page ranking algorithm based on the analysis of a hyperlink structure and a social link structure, and a communication interface attached to a page that allows real-time users to communicate with each other. By our system, users can quickly search not only for popular web pages but also for other users currently accessing them.