Akshay Java

3.8k citations
30 papers · 2.4k indexed · 1 hit paper · h-index 12

Akshay Java

28 papers receiving 2.1k citations

Hit Papers

Why we twitter1.8k200720262013201950010001.5k

Peers

Akshay Java
Comparison fields: 5 of 104
  • Communication 642
  • Statistical and Nonlinear Physics 943
  • Information Systems 838
  • Artificial Intelligence 754
  • Computer Science Applications 102
Replace Xiaodan Song with:
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Akshay Java relative to Xiaodan Song United States Xiaodan Song's profile →
Citations per field
00.5×1.5×
Xiaodan Song · 1×
Citations per year

Countries citing papers authored by Akshay Java

Since Specialization
Citations

This map shows the geographic impact of Akshay Java'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 Akshay Java with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Akshay Java more than expected).

Fields of papers citing papers by Akshay Java

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Akshay Java. 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 Akshay Java. The network helps show where Akshay Java may publish in the future.

Co-authorship network

The 20 scholars most cited alongside Akshay Java, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Akshay Java Line = papers co-authored together Akshay Java links everyone, so they are left out of the graph.

All Works

20 of 20 papers shown
#Work
1
The ICWSM 2009 Spinn3r Dataset
200988
2 200843
3 20084
4 20083
5
Mining social media communities and content
20083
6
Towards Spam Detection at Ping Servers
20077
7
Spam in Blogs and Social Media, Tutorial
20072
8 200712
9
Web 2.0 Mining: Analyzing Social Media
200711
10 20076
11 200725
12
Why we twitterbreakdown →
20071768
13 20076
14
SemNews: a semantic news framework
200614
15 200692
16 200611
17
Integrating Language Understanding Agents Into the Semantic Web
20054
18 200551
19 20037
20
Predictive Mining of Time Series Data
20022

About Akshay Java

Akshay Java is a scholar working on Statistical and Nonlinear Physics, Information Systems and Artificial Intelligence, having authored 30 papers that have together received 2.4k indexed citations. Recurring topics across this work include Complex Network Analysis Techniques (13 papers), Web Data Mining and Analysis (10 papers), Spam and Phishing Detection (9 papers), Opinion Dynamics and Social Influence (8 papers), Semantic Web and Ontologies (6 papers), Advanced Text Analysis Techniques (6 papers), Topic Modeling (5 papers) and Natural Language Processing Techniques (4 papers). The work is most often cited by research in Communication (642 citations), Statistical and Nonlinear Physics (943 citations) and Information Systems (838 citations). Akshay Java has collaborated with scholars based in United States and United Kingdom. Frequent co-authors include Tim Finin, Xiaodan Song, Belle L. Tseng, Pranam Kolari, Anupam Joshi, Tim Oates, Ian Soboroff, Sergei Nirenburg, Yun Peng and Li Ding. Their work appears in journals such as International Journal on Semantic Web and Information Systems, AI Magazine, AAS, Proceedings of the International AAAI Conference on Web and Social Media and arXiv (Cornell University).

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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