{"_id":"dv4NB8PPN6qQY4Zqb","bibbaseid":"vosoughi-roy-asemiautomaticmethodforefficientdetectionofstoriesonsocialmedia-2016","authorIDs":[],"author_short":["Vosoughi, S.","Roy, D."],"bibdata":{"bibtype":"inproceedings","type":"inproceedings","address":"Cologne, Germany","title":"A semi-automatic method for efficient detection of stories on social media","abstract":"Twitter has become one of the main sources of news for many people. As real-world events and emergencies unfold, Twitter is abuzz with hundreds of thousands of stories about the events. Some of these stories are harmless, while others could potentially be life-saving or sources of malicious rumors. Thus, it is critically important to be able to efficiently track stories that spread on Twitter during these events. In this paper, we present a novel semi-automatic tool that enables users to efficiently identify and track stories about real-world events on Twitter. We ran a user study with 25 participants, demonstrating that compared to more conventional methods, our tool can increase the speed and the accuracy with which users can track stories about real-world events. © Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.","language":"en","booktitle":"Proceedings of the 10th International Conference on Web and Social Media, ICWSM 2016","publisher":"The AAAI Press","author":[{"propositions":[],"lastnames":["Vosoughi"],"firstnames":["S."],"suffixes":[]},{"propositions":[],"lastnames":["Roy"],"firstnames":["D."],"suffixes":[]}],"year":"2016","pages":"707–710","bibtex":"@inproceedings{vosoughi_semi-automatic_2016,\n\taddress = {Cologne, Germany},\n\ttitle = {A semi-automatic method for efficient detection of stories on social media},\n\tabstract = {Twitter has become one of the main sources of news for many people. As real-world events and emergencies unfold, Twitter is abuzz with hundreds of thousands of stories about the events. Some of these stories are harmless, while others could potentially be life-saving or sources of malicious rumors. Thus, it is critically important to be able to efficiently track stories that spread on Twitter during these events. In this paper, we present a novel semi-automatic tool that enables users to efficiently identify and track stories about real-world events on Twitter. We ran a user study with 25 participants, demonstrating that compared to more conventional methods, our tool can increase the speed and the accuracy with which users can track stories about real-world events. © Copyright 2016, Association for the Advancement of Artificial Intelligence (www.aaai.org). All rights reserved.},\n\tlanguage = {en},\n\tbooktitle = {Proceedings of the 10th {International} {Conference} on {Web} and {Social} {Media}, {ICWSM} 2016},\n\tpublisher = {The AAAI Press},\n\tauthor = {Vosoughi, S. and Roy, D.},\n\tyear = {2016},\n\tpages = {707--710}\n}\n\n","author_short":["Vosoughi, S.","Roy, D."],"key":"vosoughi_semi-automatic_2016","id":"vosoughi_semi-automatic_2016","bibbaseid":"vosoughi-roy-asemiautomaticmethodforefficientdetectionofstoriesonsocialmedia-2016","role":"author","urls":{},"downloads":0},"bibtype":"inproceedings","biburl":"http://bibbase.org/zotero-group/science_et_ignorance/2114998","creationDate":"2020-04-24T08:42:39.696Z","downloads":0,"keywords":[],"search_terms":["semi","automatic","method","efficient","detection","stories","social","media","vosoughi","roy"],"title":"A semi-automatic method for efficient detection of stories on social media","year":2016,"dataSources":["RztxrSRh6LxCd8bYe"]}