ICCC

Vian Sobeeh

Job title or function

Vian Sobeeh is a member of the ICCC alumni community. Documented research areas include fake-news detection, deep learning and topic modeling.

Selected published work: “Fake News Detection Through Topic Modeling and Optimized Deep Learning with Multi-Domain Knowledge Sources” (2021). Publication details and links are listed below.

Research & Publications

Research & Publications

4 matched publications · Newest first

This list contains publications matched from publisher and author records. It may not include every publication.

2021 · Transactions on Computational Science and Computational Intelligence

Fake News Detection Through Topic Modeling and Optimized Deep Learning with Multi-Domain Knowledge Sources

Vian Sabeeh, Mohammed Zohdy, Rasha Al Bashaireh

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Start here · New researcher guide

A reading workflow, not an author-verified summary. Confirm all details in the original publication.

  1. Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
  2. Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
  3. Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
  4. Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
  5. Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.

For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.

2020 · Proceedings of the 2020 the 4th International Conference on Information System and Data Mining

Twitter Data Collection and Extraction

Rasha Al Bashaireh, Mohamed Zohdy, Vian Sabeeh

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Start here · New researcher guide

A reading workflow, not an author-verified summary. Confirm all details in the original publication.

  1. Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
  2. Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
  3. Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
  4. Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
  5. Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.

For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.

2019 · 2019 International Conference on Computational Science and Computational Intelligence (CSCI)

Towards a New Indicator for Evaluating Universities Based on Twitter Sentiment Analysis

Rasha Al Bashaireh, Vian Sabeeh, Mohammed Zohdy

View Publication
Start here · New researcher guide

A reading workflow, not an author-verified summary. Confirm all details in the original publication.

  1. Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
  2. Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
  3. Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
  4. Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
  5. Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.

For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.

2019 · 2019 International Conference on Computational Science and Computational Intelligence (CSCI)

Enhancing the Fake News Detection by Applying Effective Feature Selection Based on Semantic Sources

Vian Sabeeh, Mohammed Zohdy, Rasha Al Bashaireh

View Publication
Start here · New researcher guide

A reading workflow, not an author-verified summary. Confirm all details in the original publication.

  1. Check the fit. Read the abstract and introduction. Write down the research question and explain how it relates to your idea.
  2. Understand the method. Identify the approach, assumptions, data and evaluation measures in the paper.
  3. Check reproducibility. Look for linked code, datasets and supplementary material. Availability has not been verified by ICCC.
  4. Find your next question. Read limitations and future work. Propose one extension and check newer literature before claiming a research gap.
  5. Plan a first experiment. Define a baseline, the change you will test and a measurable outcome. Discuss feasibility with your supervisor.

For questions or collaboration, visit the member profile and use a listed contact channel. Authorship and collaboration require agreement.
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