The Impact of Iraqi Politicians' Use of Twitter on Public Political Awareness

Turki Hasan Najm; Leith Bader Yusuf; تركي حسن نجم; ليث بدر يوسف

doi:10.33282/abaa.v15i60.933

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Publication Date

Wed Jun 28 2023

Journal Name

Al–bahith Al–a'alami

Volume

15

Issue Number

60

DOI

10.33282/abaa.v15i60.933

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The Impact of Iraqi Politicians' Use of Twitter on Public Political Awareness

Social media

Twitter

Political awareness development

Turki Hasan Najm

Leith Bader Yusuf

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This research investigates the impact of Iraqi politicians' utilization of Twitter as an interactive media tool to communicate their positions and perspectives on political events. Twitter has become a significant platform for dialogue and interactive discussions. The survey method, specifically the descriptive approach, was employed to answer research questions and achieve objectives. A sample of 100 Iraqi Twitter users was selected, considering demographic variables such as gender, age, and educational background, during the period from September 15 to October 1, 2022.

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Publication Date

Fri Oct 31 2025

Journal Name

Sustainability

Upgrading Sustainability in Clean Energy: Optimization for Proton Exchange Membrane Fuel Cells Using Heterogeneous Comprehensive Learning Bald Eagle Search Algorithm

proton exchange membrane fuel cell

optimization algorithm

parameter estimation

bald eagle search

heterogeneous comprehensive learning

sustainable development

Ahmed K.

Ali Nasser

Mudhar A.

Sarmad

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Clean energy applications widely recognize Proton Exchange Membrane Fuel Cells (PEMFCs) for their high efficiency and environmental compatibility. Accurate parameter identification of PEMFC models is essential for enhancing system performance and reliability, particularly under dynamic operating conditions. This paper presents a novel optimization-based approach called Heterogeneous Comprehensive Learning-Bald Eagle Search (HCLBES) with enhanced exploration and exploitation capabilities for the effective modeling of PEMFC. The algorithm combines the exploration strength of the Bald Eagle Search with comprehensive learning and heterogeneity mechanisms to achieve a balanced global and local search space. In this algorithm, the number

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Publication Date

Thu Jul 30 2026

Journal Name

International Journal Of Robotics And Control Systems

Integrating Multimodal Emotion Recognition with Deep Q-Learning for Adaptive Social Robot Interaction

Adaptive Response Generation

Deep Q-Learning

Emotionally Intelligent Social Robots

Human–Robot Interaction in Healthcare

Multimodal Emotion Recognition

Multimodal Fusion Architecture

Nada

Saleh

Raed

Aseel

Muhannad

Laith

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Publication Date

Fri Nov 21 2025

Journal Name

Journal Of Advances In Information Technology

Towards Accurate SDG Research Categorization: A Hybrid Deep Learning Approach Using Scopus Metadata

text classification

Sustainable Development Goals (SDGs)

deep learning

hybrid bidirectional Long Short-Term Memory-Convolutional Neural Network (LSTM-CNN)

Global Vector (GloVe) embeddings

Jalal Sadoon Hameed

Furat N.

Mohammed

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The complexity and variety of language included in policy and academic documents make the automatic classification of research papers based on the United Nations Sustainable Development Goals (SDGs) somewhat difficult. Using both pre-trained and contextual word embeddings to increase semantic understanding, this study presents a complete deep learning pipeline combining Bidirectional Long Short-Term Memory (BiLSTM) and Convolutional Neural Network (CNN) architectures which aims primarily to improve the comprehensibility and accuracy of SDG text classification, thereby enabling more effective policy monitoring and research evaluation. Successful document representation via Global Vector (GloVe), Bidirectional Encoder Representations from Tra

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Publication Date

Sat Oct 01 2016

Journal Name

Journal Of Theoretical And Applied Information Technology

Factors affecting global virtual teams’ performance in software projects

Today the trend is to perform software development work via distributed geographical area among team

individual or even as an organization. However

due to the global market and international presence of many companies

there is a need to implement a global virtual teams. The global virtual team members are gradually engaged in globalized business environments across space

time and organizational boundaries via information and communication technologies. A global virtual team relies on communication

collaboration

and information exchange are the most important criteria in global virtual teams’ operations. The purpose of this paper is to answer two research questions. The first research question is to identify the factors affecting global virtual teams’ performance. A systematic literature review was conducted to answer the first research question. The second research question is on what the rank of the factor affecting the global virtual teams’ performance according to their level of effect on global virtual teams’ performance. Online survey was conducted within 103 developers and IT managers from eight IT companies to answer the second research question. The Statistical Package for Social Science (SPSS 22) was used to analyze the collected data. In this study

we investigated factors that affect global virtual teams’ performance

factors considered include cultural differences

language problems

time-zone differences

team size

technical problems

lack of trust

lack of sufficient training

and ICT problems. Also the findings indicated that lack of sufficient training is the highest level of effect on global virtual teams’ performance. On the other hand

Ali Yahya Gheni

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(24)

Publication Date

Sat May 31 2025

Journal Name

3rd International Scientific Conference For Human And Social Studies And Epistemological Challenges

Frankenstein Complex in Daniel H. Wilson's Robopocalypse ( ): Artificial Intelligence Conspiracies

With the advent of technology

the fear of losing control has consistently accompanied humanity. While humans have discovered

invented

and created many remarkable things

they have also been haunted by the possibility of their creations turning against them. This fear

often referred to as the Frankenstein Complex

derives its name from Mary Shelley's Frankenstein (􀀔􀀛􀀔􀀛)

in which Dr. Frankenstein's creation ultimately destroys its maker. The Frankenstein Complex embodies the subconscious fear of artificial intelligence (AI) surpassing and potentially dominating humankind. This apprehension has inspired numerous literary works

including Daniel H. Wilson’s novels. The present study examines the widespread fear of AI

which has fueled conspiracy theories in literature. These theories have not only amplified public anxiety but also hindered understanding among those with limited knowledge of AI and robotics. Dr. Wilson

a robotics expert

uses his imagination as a driving force for both his writing and his inventions. The research focuses on incidents leading to the rise of robots

the concept of the New War

how it was fought

and how it concluded. By comparing

contrasting

and analyzing literary elements and devices with prominent conspiracy theories

the study highlights the interplay between fiction and scientific development. The researchers conclude that while many conspiracy theories contain elements of truth

they often inspire scientists to explore them further. Additionally

some conspiracy theories warrant serious consideration. The study recommends acknowledging the Frankenstein Complex while maintaining faith in the potential benefits of artificial intelligence.

Ansam

Mayada

Zahraa

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