Countries citing papers authored by Radhika Mamidi
Since
Specialization
Citations
This map shows the geographic impact of Radhika Mamidi'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 Radhika Mamidi with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Radhika Mamidi more than expected).
This network shows the impact of papers produced by Radhika Mamidi. 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 Radhika Mamidi. The network helps show where Radhika Mamidi may publish in the future.
Co-authorship network of co-authors of Radhika Mamidi
This figure shows the co-authorship network connecting the top 25 collaborators of Radhika Mamidi.
A scholar is included among the top collaborators of Radhika Mamidi 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 Radhika Mamidi. Radhika Mamidi is excluded from
the visualization to improve readability, since they are connected to all nodes in the network.
Mamidi, Radhika, et al.. (2020). A Novel Annotation Schema for Conversational Humor: Capturing the Cultural Nuances in Kanyasulkam. 34–47.3 indexed citations
7.
Mamidi, Radhika, et al.. (2020). Dataset Creation and Evaluation of Aspect Based Sentiment Analysis in Telugu, a Low Resource Language. Language Resources and Evaluation. 5017–5024.5 indexed citations
8.
Mamidi, Radhika, et al.. (2018). Resource Creation Towards Automated Sentiment Analysis in Telugu (a low resource language) and Integrating Multiple Domain Sources to Enhance Sentiment Prediction.. Language Resources and Evaluation.13 indexed citations
9.
Mamidi, Radhika, et al.. (2018). Predicting the Genre and Rating of a Movie Based on its Synopsis.. Waseda University Repository (Waseda University).7 indexed citations
10.
Mamidi, Radhika, et al.. (2018). Political Discourse Analysis : A Case Study of 2014 Andhra Pradesh State Assembly Election of Interpersonal Speech Choices. Waseda University Repository (Waseda University).3 indexed citations
11.
Mamidi, Radhika, et al.. (2016). Enhanced Sentiment Classification of Telugu Text using ML Techniques.. International Joint Conference on Artificial Intelligence. 29–34.23 indexed citations
12.
Mamidi, Radhika, et al.. (2016). Towards Building a SentiWordNet for Tamil. 30–35.8 indexed citations
13.
Mamidi, Radhika, et al.. (2016). Multimodal Sentiment Analysis of Telugu Songs.. International Joint Conference on Artificial Intelligence. 48–52.11 indexed citations
14.
Mamidi, Radhika, et al.. (2015). Statistical Sandhi Splitter and its Effect on NLP Applications. Recent Advances in Natural Language Processing. 313–319.1 indexed citations
15.
Mamidi, Radhika, et al.. (2015). A Semi Supervised Dialog Act Tagging for Telugu. 376–383.2 indexed citations
16.
Akula, Arjun, et al.. (2015). Classification of Attributes in a Natural Language Query into Different SQL Clauses. Recent Advances in Natural Language Processing. 497–506.8 indexed citations
17.
Mamidi, Radhika, et al.. (2015). Resolution of Pronominal Anaphora for Telugu Dialogues.. 183–188.2 indexed citations
18.
Mamidi, Radhika, et al.. (2014). Identification of Karaka relations in an English sentence. 146–149.1 indexed citations
19.
Akula, Arjun, Rajeev Sangal, & Radhika Mamidi. (2013). A Novel Approach Towards Incorporating Context Processing Capabilities in NLIDB System. International Joint Conference on Natural Language Processing. 1216–1222.5 indexed citations
20.
Sangal, Rajeev, et al.. (2013). Stance Classification in Online Debates by Recognizing Users' Intentions. Annual Meeting of the Special Interest Group on Discourse and Dialogue. 61–69.11 indexed citations
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.