Angelika Maag

1.2k citations
22 papers · 795 indexed · 1 hit paper · h-index 7
Topics
Augmented Reality Applications (4 papers)Surgical Simulation and Training (3 papers)IoT and Edge/Fog Computing (3 papers)
Partner nations
AustraliaMalaysiaIraq

In The Last Decade

Angelika Maag

21 papers receiving 759 citations

Hit Papers

Deep Learning for Aspect-Based Sentiment Analysis: A Comp...20182026202020232018100200300400

Peers

Angelika Maag
Comparison fields: 5 of 100
  • Artificial Intelligence 476
  • Information Systems 213
  • Computer Science Applications 125
  • Sociology and Political Science 96
  • Education 93
Replace Anjo Anjewierden with:
Anjo Anjewierden Netherlands
Yohan Jo United States
Ayman G. Fayoumi Saudi Arabia
Nazlia Omar Malaysia
Krishna Madhavan United States
Álvaro Ortigosa Spain
Rosa M. Carro Spain
Hayden Wimmer United States
Swapna Gottipati Singapore
Jacqueline Bourdeau Canada
Angelika Maag relative to Anjo Anjewierden Netherlands Anjo Anjewierden's profile →
Citations per field
00.5×6.4×
Anjo Anjewierden · 1×
Citations per year

Countries citing papers authored by Angelika Maag

Since Specialization
Citations

This map shows the geographic impact of Angelika Maag's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Angelika Maag with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Angelika Maag more than expected).

Fields of papers citing papers by Angelika Maag

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Angelika Maag. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Angelika Maag. The network helps show where Angelika Maag may publish in the future.

Co-authorship network of co-authors of Angelika Maag

This figure shows the co-authorship network connecting the top 25 collaborators of Angelika Maag. A scholar is included among the top collaborators of Angelika Maag based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Angelika Maag. Angelika Maag is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
#WorkIndexed citations
1 7
2 1
3 1
4 1
5 3
6 2
7 2
8 2
9 1
10 1
11 4
12 2
13 195
14 22
15 4
16 1
17
Deep Learning for Aspect-Based Sentiment Analysis: A Comparative Reviewbreakdown →
423
18 97
19 5
20 3

About Angelika Maag

Angelika Maag is a scholar working on Human-Computer Interaction, Computer Vision and Pattern Recognition and Information Systems and Management, having authored 22 papers that have together received 795 indexed citations. Recurring topics across this work include Augmented Reality Applications (4 papers), Surgical Simulation and Training (3 papers) and IoT and Edge/Fog Computing (3 papers). The work is most often cited by research in Computer Science Applications (125 citations), Artificial Intelligence (476 citations) and Information Systems (213 citations). Angelika Maag has collaborated with scholars based in Australia, Malaysia and Iraq. Frequent co-authors include Abeer Alsadoon, P. W. C. Prasad, Siong Hoe Lau, Amr Elchouemi, Hui Yang, Omar Hisham Alsadoon and Tarik A. Rashid. Their work appears in journals such as Expert Systems with Applications, Computers & Education and Multimedia Tools and Applications.

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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