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Learning Contextual Knowledge Structures from the Web for Facilitating Semantic Interpretation of Tweets

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Proceedings of International Conference on Recent Advancement on Computer and Communication

Part of the book series: Lecture Notes in Networks and Systems ((LNNS,volume 34))

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Abstract

Tweet analysis can provide valuable insight into societal issues and opinions. The terse, cryptic tweets, however, cannot be interpreted on face value. Interpretation assumes contextual knowledge. We propose a novel methodology of extracting structured contextual knowledge for popular topics/events and building knowledge structures using mining and computational linguistics techniques. We crunch relevant context contents from online sources and structure the same as contextual knowledge structures (CKSs). These automatically extracted CKS are (a) structured as subject–predicate–object triples, (b) they are relevant because they are built by mining contextual Web content, and (c) they are scalable to ontology and can be used for training classifiers. We demonstrate the feasibility and effectiveness of this methodology with an experiment which captures tweets of Indian political leaders, taps the related Web content, and transforms the same into CKS. The novel contribution of this work is its synergistic approach which combines acquisition, organization, and summarization with scalability to contextual ontology for social media analytics.

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Authors and Affiliations

  1. Department of Computer Science and Applications, Bangalore University, Bengaluru, India

    Nazura Javed & Muralidhara B. L.

Authors
  1. Nazura Javed
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  2. Muralidhara B. L.
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Corresponding author

Correspondence to Nazura Javed .

Editor information

Editors and Affiliations

  1. Computer Science and Engineering, Technocrats Institute of Technology, Bhopal, Madhya Pradesh, India

    Basant Tiwari

  2. Computer Science and Engineering, DSPM IIIT, Naya Raipur, Chhattisgarh, India

    Vivek Tiwari

  3. Department of Mathematics, Sungkyunkwan University, Suwon, Korea (Republic of)

    Kinkar Chandra Das

  4. Microsoft Innovation Academy, Computer Science and Engineering, Sri Aurobindo Institute of Technology, Indore, Madhya Pradesh, India

    Durgesh Kumar Mishra

  5. Department of Mathematics, South Asian University, New Delhi, Delhi, India

    Jagdish C. Bansal

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Javed, N., B. L., M. (2018). Learning Contextual Knowledge Structures from the Web for Facilitating Semantic Interpretation of Tweets. In: Tiwari, B., Tiwari, V., Das, K., Mishra, D., Bansal, J. (eds) Proceedings of International Conference on Recent Advancement on Computer and Communication . Lecture Notes in Networks and Systems, vol 34. Springer, Singapore. https://doi.org/10.1007/978-981-10-8198-9_34

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  • DOI: https://doi.org/10.1007/978-981-10-8198-9_34

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8197-2

  • Online ISBN: 978-981-10-8198-9

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