SMC Chapter Seminar on Comparative Study on Ground Truth Inference Algorithms based on Manually Labeled Social Media Data

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Comparative Study on Ground Truth Inference Algorithms based on Manually Labeled Social Media Data

 

Mr. Xiaoyu Sean Lu, Ph.D. Candidate

 

Time: 10:00 am -11:00 am, July 15, 2019

Room: ECEC 202

 

Abstract

 

Abstract—In the booming information era, smart devices such as smart phones accompany peoples’ lives all the time. Social media platforms provide users with uninterrupted communication and information acquisition including posting users’ feelings and sharing ideas. This study focuses on short texts posted by users. Their true meaning is defined as ground truth. However, acquiring it from the users directly is extremely difficult and time-consuming. In other words, in many cases, short texts do not have their ground truth. Thus, we deal with a no ground truth problem. In this work, we ask for labelers to label short texts completely based on their own judgment of these texts. Two ground truth inference approaches, majority voting (MV) and positive label frequency threshold (PLAT), integrate the labels from different labelers and deduce the ground truth. We then analyze which one better suits for labeling unlabeled short texts. The work is of great significance in helping us obtain useful knowledge from massive social media data.

 

Bio-sketch

Xiaoyu Sean Lu (S’14) received the B.S degree from Nanjing University of Technology, Nanjing, China, in 2011 and the M.S from New Jersey Institute of Technology, Newark, NJ, USA, in 2015. He is now pursuing the Ph.D. degree in the Department of Electrical and Computer Engineering, New Jersey Institute of Technology, Newark, NJ, USA. His current research interests include social media data analysis, data processing, data mining, Petri nets modeling of microgrids, and Petri nets applications in power systems. He has published several papers and is active reviewer for several conferences and journals.


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  • Newark, New Jersey
  • United States
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  • Starts 01 July 2019 07:00 PM UTC
  • Ends 14 July 2019 07:00 PM UTC
  • No Admission Charge

  Speakers

Mr. Sean Lu