Strategy for Processing and Analyzing Social Media Data Streams in Emergencies

被引:0
|
作者
Moi, Matthias [1 ]
Friberg, Therese [1 ]
Marterer, Robin [1 ]
Reuter, Christian [2 ]
Ludwig, Thomas [2 ]
机构
[1] Univ Paderborn, CIK, Paderborn, Germany
[2] Univ Siegen, Inst Informat Syst, Siegen, Germany
关键词
social media; information gathering; information mining; ontology; emergency services; emergencies; information quality; information visualisation;
D O I
暂无
中图分类号
TP301 [理论、方法];
学科分类号
081202 ;
摘要
People are using social media to a greater extent, particularly in emergency situations. However, approaches for processing and analyzing the vast quantities of data produced currently lag far behind. In this paper we discuss important steps, and the associated challenges, for processing and analyzing social media in emergencies. In our research project EmerGent, a huge volume of low-quality messages will be continuously gathered from a variety of social media services such as Facebook or Twitter. Our aim is to design a software system that will process and analyze social media data, transforming the high volume of noisy data into a low volume of rich content that is useful to emergency personnel. Therefore, suitable techniques are needed to extract and condense key information from raw social media data, allowing detection of relevant events and generation of alerts pertinent to emergency personnel.
引用
收藏
页码:42 / 48
页数:7
相关论文
共 50 条
  • [1] IBM Streams Processing Language: Analyzing Big Data in motion
    Hirzel, M.
    Andrade, H.
    Gedik, B.
    Jacques-Silva, G.
    Khandekar, R.
    Kumar, V.
    Mendell, M.
    Nasgaard, H.
    Schneider, S.
    Soule, R.
    Wu, K. -L.
    [J]. IBM JOURNAL OF RESEARCH AND DEVELOPMENT, 2013, 57 (3-4)
  • [2] A Survey on Event Tracking in Social Media Data Streams
    Han, Zixuan
    Shi, Leilei
    Liu, Lu
    Jiang, Liang
    Fang, Jiawei
    Lin, Fanyuan
    Zhang, Jinjuan
    Panneerselvam, John
    Antonopoulos, Nick
    [J]. BIG DATA MINING AND ANALYTICS, 2024, 7 (01): : 217 - 243
  • [3] Efficient Event Detection in Social Media Data Streams
    Sun, Xiang
    Wu, Yan
    Liu, Lu
    Panneerselvam, John
    [J]. CIT/IUCC/DASC/PICOM 2015 IEEE INTERNATIONAL CONFERENCE ON COMPUTER AND INFORMATION TECHNOLOGY - UBIQUITOUS COMPUTING AND COMMUNICATIONS - DEPENDABLE, AUTONOMIC AND SECURE COMPUTING - PERVASIVE INTELLIGENCE AND COMPUTING, 2015, : 1712 - 1718
  • [4] Parallel Strategy for the Large-Scale Data Streams Processing
    Yuan, Ya-Juan
    Ma, Guo-Jie
    [J]. PROCEEDINGS OF THE 2016 INTERNATIONAL CONFERENCE ON COMPUTER ENGINEERING AND INFORMATION SYSTEMS, 2016, 52 : 232 - 234
  • [5] Analyzing Social Media Opinions Using Data Analytics
    Najadat, Hassan M.
    Alzu'bi, Amal A.
    Shatnawi, Farah
    Rawashdeh, Saif
    Eyadat, Walaa
    [J]. 2020 11TH INTERNATIONAL CONFERENCE ON INFORMATION AND COMMUNICATION SYSTEMS (ICICS), 2020, : 266 - 271
  • [6] A Framework for Analyzing Big Social Data and Modelling Emotions in Social Media
    Perikos, Isidoros
    Hatzilygeroudis, Ioannis
    [J]. 2018 IEEE FOURTH INTERNATIONAL CONFERENCE ON BIG DATA COMPUTING SERVICE AND APPLICATIONS (IEEE BIGDATASERVICE 2018), 2018, : 80 - 84
  • [7] Imagine: Media processing with streams
    Khailany, B
    Dally, WJ
    Kapasi, UJ
    Mattson, P
    Namkoong, J
    Owens, JD
    Towles, B
    Chang, A
    Rixner, S
    [J]. IEEE MICRO, 2001, 21 (02) : 35 - 46
  • [8] Dimensionality reduction in the context of dynamic social media data streams
    Moritz Heusinger
    Christoph Raab
    Frank-Michael Schleif
    [J]. Evolving Systems, 2022, 13 : 387 - 401
  • [9] Dimensionality reduction in the context of dynamic social media data streams
    Heusinger, Moritz
    Raab, Christoph
    Schleif, Frank-Michael
    [J]. EVOLVING SYSTEMS, 2022, 13 (03) : 387 - 401
  • [10] The EmerGent project: Emergency Management in Social Media Generation Dealing with Big Data from Social Media Data Streams
    Greenlaw, Reynold
    Muddiman, Andrew
    Friberg, Therese
    Moi, Matthias
    Cristaldi, Massimo
    Ludwig, Thomas
    Reuter, Christian
    [J]. 2014 IEEE/ACM 7TH INTERNATIONAL CONFERENCE ON UTILITY AND CLOUD COMPUTING (UCC), 2014, : 687 - 689