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Social Health Signals, Ashutosh Sopan Jadhav, Swapnil Soni, Amit P. Sheth
Social Health Signals, Ashutosh Sopan Jadhav, Swapnil Soni, Amit P. Sheth
Kno.e.sis Publications
Recently Twitter, has emerged as one of the primary medium for sharing and seeking of the latest information related to variety of the topics including health information. Recently, Twitter has emerged as one of the primary mediums for sharing and seeking the latest information related to a variety of topics, including health information. Although Twitter is an excellent information source, identification of useful information from the deluge of tweets is one of the major challenge. Twitter search is limited to keyword based techniques to retrieve information for a given query and sometimes the results do not contain real-time information. Moreover, …
Domain Specific Document Retrieval Framework For Real-Time Social Health Data, Swapnil Soni
Domain Specific Document Retrieval Framework For Real-Time Social Health Data, Swapnil Soni
Kno.e.sis Publications
With the advent of the web search and microblogging, the percentage of Online Health Information Seekers (OHIS) using these online services to share and seek health real-time information has in- creased exponentially. OHIS use web search engines or microblogging search services to seek out latest, relevant as well as reliable health in- formation. When OHIS turn to microblogging search services to search real-time content, trends and breaking news, etc. the search results are not promising. Two major challenges exist in the current microblogging search engines are keyword based techniques and results do not contain real-time information. To address these challenges, …
Domain Specific Document Retrieval Framework On Near Real-Time Social Health Data, Swapnil Soni
Domain Specific Document Retrieval Framework On Near Real-Time Social Health Data, Swapnil Soni
Kno.e.sis Publications
With the advent of web search and microblogging, the percentage of Online Health Information Seekers (OHIS) using these services to share and seek health information in real-time has increased exponentially. Recently, Twitter has emerged as one of the primary mediums for sharing and seeking of the latest information related to a variety of topics, including health information. Although Twitter is an excellent information source, the identification of useful information from the deluge of tweets is one of the major challenges. Twitter search is limited to keyword-based techniques to retrieve information for a given query and sometimes the results do not …
Knowledge Enabled Location Prediction Of Twitter Users, Revathy Krishnamurthy
Knowledge Enabled Location Prediction Of Twitter Users, Revathy Krishnamurthy
Browse all Theses and Dissertations
As the popularity of online social networking sites such as Twitter and Facebook continues to rise, the volume of textual content generated on the web is increasing rapidly. The mining of user generated content in social media has proven effective in domains ranging from personalization and recommendation systems to crisis management. These applications stand to be further enhanced by incorporating information about the geo-position of social media users in their analysis. Due to privacy concerns, users are largely reluctant to share their location information. As a consequence of this, researchers have focused on automatic inferencing of location information from the …
Knowledge Enabled Approach To Predict The Location Of Twitter Users, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan
Knowledge Enabled Approach To Predict The Location Of Twitter Users, Revathy Krishnamurthy, Pavan Kapanipathi, Amit P. Sheth, Krishnaprasad Thirunarayan
Kno.e.sis Publications
Knowledge bases have been used to improve performance in applications ranging from web search and event detection to entity recognition and disambiguation. More recently, knowledge bases have been used to analyze social data. A key challenge in social data analysis has been the identification of the geographic location of online users in a social network such as Twitter. Existing approaches to predict the location of users, based on their tweets, rely solely on social media features or probabilistic language models. These approaches are supervised and require large training dataset of geo-tagged tweets to build their models. As most Twitter users …
Features For Ranking Tweets Based On Credibility And Newsworthiness, Jacob W. Ross
Features For Ranking Tweets Based On Credibility And Newsworthiness, Jacob W. Ross
Browse all Theses and Dissertations
We create a robust and general feature set for learning to rank algorithms that rank tweets based on credibility and newsworthiness. In previous works, it has been demonstrated that when the training and testing data are from two distinct time periods, the ranker performs poorly. We improve upon previous work by creating a feature set that does not over fit a particular year or set of topics. This is critical given how people utilize social media changes as time progresses, and the topics discussed vary. In addition, we are constantly gaining new tweet data. Thus, it is important to be …
Domain-Specific Document Retrieval Framework For Near Real-Time Social Health Data, Swapnil Soni
Domain-Specific Document Retrieval Framework For Near Real-Time Social Health Data, Swapnil Soni
Browse all Theses and Dissertations
With the advent of web search and microblogging, the percentage of Online Health Information Seekers (OHIS) using these services to share and seek health information in real-time has increased exponentially. Recently, Twitter has emerged as one of the primary mediums for sharing and seeking of the latest information related to a variety of topics, including health information. Although Twitter is an excellent information source, the identification of useful information from the deluge of tweets is one of the major challenges. Twitter search is limited to keyword-based techniques to retrieve information for a given query and sometimes the results do not …