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1
Personalized Prediction of Suicide Risk for Web-based Intervention
In: Krishnaprasad Thirunarayan (2019)
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Personalized Prediction of Suicide Risk for Web-based Intervention
In: Amit P. Sheth (2019)
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3
Personalized Prediction of Suicide Risk for Web-based Intervention
In: Kno.e.sis Publications (2018)
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4
RQUERY: Rewriting Natural Language Queries on Knowledge Graphs to Alleviate the Vocabulary Mismatch Problem
In: Kno.e.sis Publications (2017)
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5
What Kind of #Communication is Twitter? A Psycholinguistic Perspective on Communication in Twitter for the Purpose of Emergency Coordination
In: Valerie Shalin (2017)
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6
What Kind of #Conversation is Twitter? Mining #Psycholinguistic Cues for Emergency Coordination
In: Valerie Shalin (2017)
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7
RQUERY: Rewriting Natural Language Queries on Knowledge Graphs to Alleviate the Vocabulary Mismatch Problem
In: Amit P. Sheth (2017)
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8
Intent Classification of Short-Text on Social Media
In: Valerie Shalin (2017)
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9
Context-Aware Semantic Association Ranking
In: Amit P. Sheth (2016)
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10
ezDI's Semantics-Enhanced Linguistic, NLP, and ML Approach for Health Informatics
In: Amit P. Sheth (2016)
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11
Intent Classification of Short-Text on Social Media
In: Amit P. Sheth (2016)
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12
Intent Classification of Short-Text on Social Media
In: Krishnaprasad Thirunarayan (2016)
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13
FACES: Diversity-Aware Entity Summarization using Incremental Hierarchical Conceptual Clustering
In: Kno.e.sis Publications (2015)
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14
Context-Driven Automatic Subgraph Creation for Literature-Based Discovery
In: Kno.e.sis Publications (2015)
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15
Identifying Seekers and Suppliers in Social Media Communities to Support Crisis Coordination
In: John M. Flach (2015)
Abstract: Effective crisis management has long relied on both the formal and informal response communities. Social media platforms such as Twitter increase the participation of the informal response community in crisis response. Yet, challenges remain in realizing the formal and informal response communities as a cooperative work system. We demonstrate a supportive technology that recognizes the existing capabilities of the informal response community to identify needs (seeker behavior) and provide resources (supplier behavior), using their own terminology. To facilitate awareness and the articulation of work in the formal response community, we present a technology that can bridge the differences in terminology and understanding of the task between the formal and informal response communities. This technology includes our previous work using domain-independent features of conversation to identify indications of coordination within the informal response community. In addition, it includes a domain-dependent analysis of message content (drawing from the ontology of the formal response community and patterns of language usage concerning the transfer of property) to annotate social media messages. The resulting repository of annotated messages is accessible through our social media analysis tool, Twitris. It allows recipients in the formal response community to sort on resource needs and availability along various dimensions including geography and time. Thus, computation indexes the original social media content and enables complex querying to identify contents, players, and locations. Evaluation of the computed annotations for seeker-supplier behavior with human judgment shows fair to moderate agreement. In addition to the potential benefits to the formal emergency response community regarding awareness of the observations and activities of the informal response community, the analysis serves as a point of reference for evaluating more computationally intensive efforts and characterizing the patterns of language behavior during a crisis.
Keyword: Bioinformatics; Communication; Communication Technology and New Media; Computer Sciences; Cooperative Crisis Response; Coordination; Crisis Informatics; Crisis Response Coordination; Databases and Information Systems; Life Sciences; Organizational Sensemaking; OS and Networks; Physical Sciences and Mathematics; Psycholinguistics; Psychology; Science and Technology Studies; Seeker-Supplier Behavior; Semantic Web; Social and Behavioral Sciences; Spatio-Temporal Analysis; Twitris
URL: https://works.bepress.com/john_flach/20
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16
Comparative Analysis of Online Health Queries Originating from Personal Computers and Smart Devices on a Consumer Health Information Portal
In: Ashutosh Jadhav (2015)
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17
An Analysis of Mayo Clinic Search Query Logs for Cardiovascular Diseases
In: Ashutosh Jadhav (2015)
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18
Online Information Searching for Cardiovascular Diseases: An Analysis of Mayo Clinic Search Query Logs
In: Ashutosh Jadhav (2015)
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19
What Kind of #Conversation is Twitter? Mining #Psycholinguistic Cues for Emergency Coordination
In: John M. Flach (2015)
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20
Intent Classification of Short-Text on Social Media
In: Kno.e.sis Publications (2015)
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