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Social big data: Recent achievements and new challenges.

Gema Bello-Orgaz1, Jason J Jung2, David Camacho1

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Big data frameworks like Apache Hadoop and Spark enable efficient data mining and machine learning. This paper reviews methodologies for data mining and information fusion in social media and social networks.

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Big dataData miningSocial mediaSocial networksSocial-based frameworks and applications

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Area of Science:

  • Data Science
  • Computer Science
  • Information Science

Background:

  • Big data is crucial across research areas like data mining, machine learning, and social networks.
  • Frameworks such as Apache Hadoop and Spark facilitate massive data processing using the MapReduce paradigm.
  • Libraries like Mahout and SparkMLib support the development of efficient machine learning applications.

Purpose of the Study:

  • To review new methodologies for efficient data mining and information fusion from social media.
  • To explore emerging applications and frameworks within the social networks, social media, and big data paradigms.
  • To address challenges in big data processing, storage, representation, and utilization for pattern mining and user behavior analysis.

Main Methods:

  • Literature review of existing big data technologies and machine learning algorithms.
  • Analysis of frameworks like Apache Hadoop, Spark, Mahout, and SparkMLib.
  • Examination of challenges and solutions in social media data processing and analysis.

Main Results:

  • Big data technologies combined with machine learning offer efficient data utilization.
  • New challenges arise in social media data processing, storage, representation, and analysis.
  • Emerging methodologies and frameworks are crucial for extracting insights from social data.

Conclusions:

  • The integration of big data and machine learning is transforming various research domains.
  • Efficient data mining and information fusion from social media require advanced methodologies and frameworks.
  • Continued research in this area is vital for understanding complex social dynamics and user behaviors.