---
title: "SemEval 2014 — all accepted papers — the most cited first"
description: "All 149 papers of SemEval 2014 · page 1 of 2, the most cited first; those with our summary link to it."
canonical: "https://research.elamur.ai/free/en/venues/semeval/2014/papers/"
---
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# SemEval 2014: all accepted papers

149 papers · page 1 of 2 · the most cited first · [← SemEval 2014](https://md.research.elamur.ai/free/en/venues/semeval/2014/)

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1. **[AI-KU: Using Co-Occurrence Modeling for Semantic Similarity ↗](https://aclanthology.org/S14-2011/)**Osman Başkaya
2. **[ASAP: Automatic Semantic Alignment for Phrases ↗](https://aclanthology.org/S14-2013/)**Ana Alves, Adriana Ferrugento, Mariana Lourenço et al.
3. **[AT&T: The Tag&Parse Approach to Semantic Parsing of Robot Spatial Commands ↗](https://aclanthology.org/S14-2014/)**Svetlana Stoyanchev, Hyuckchul Jung, John Chen et al.
4. **[AUEB: Two Stage Sentiment Analysis of Social Network Messages ↗](https://aclanthology.org/S14-2015/)**Rafael Michael Karampatsis, John Pavlopoulos, Prodromos Malakasiotis
5. **[Alpage: Transition-based Semantic Graph Parsing with Syntactic Features ↗](https://aclanthology.org/S14-2012/)**Corentin Ribeyre, Eric Villemonte de la Clergerie, Djamé Seddah
6. **[BUAP: Evaluating Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment](https://md.research.elamur.ai/free/en/papers/leon-2014-buap-evaluating-compositional-distributional-semantic/)**Saúl León, Darnes Vilariño, David Pinto et al.*our summary*
7. **[BUAP: Evaluating Features for Multilingual and Cross-Level Semantic Textual Similarity ↗](https://aclanthology.org/S14-2022/)**Darnes Vilariño, David Pinto, Saúl León et al.
8. **[BUAP: Polarity Classification of Short Texts ↗](https://aclanthology.org/S14-2023/)**David Pinto, Darnes Vilariño, Saul León et al.
9. **[Bielefeld SC: Orthonormal Topic Modelling for Grammar Induction ↗](https://aclanthology.org/S14-2016/)**John P. McCrae, Philipp Cimiano
10. **[Biocom Usp: Tweet Sentiment Analysis with Adaptive Boosting Ensemble ↗](https://aclanthology.org/S14-2017/)**Nádia Silva, Estevam Hruschka, Eduardo Hruschka
11. **[Biocom Usp: Tweet Sentiment Analysis with Adaptive Boosting Ensemble ↗](https://aclanthology.org/S14-2018/)**Nádia Silva, Estevam Hruschka, Eduardo Hruschka
12. **[BioinformaticsUA: Concept Recognition in Clinical Narratives Using a Modular and Highly Efficient Text Processing Framework ↗](https://aclanthology.org/S14-2019/)**Sérgio Matos, Tiago Nunes, José Luís Oliveira
13. **[Blinov: Distributed Representations of Words for Aspect-Based Sentiment Analysis at SemEval 2014 ↗](https://aclanthology.org/S14-2020/)**Pavel Blinov, Eugeny Kotelnikov
14. **[CECL: a New Baseline and a Non-Compositional Approach for the Sick Benchmark ↗](https://aclanthology.org/S14-2024/)**Yves Bestgen
15. **[CISUC-KIS: Tackling Message Polarity Classification with a Large and Diverse Set of Features ↗](https://aclanthology.org/S14-2025/)**João Leal, Sara Pinto, Ana Bento et al.
16. **[CMU: Arc-Factored, Discriminative Semantic Dependency Parsing ↗](https://aclanthology.org/S14-2027/)**Sam Thomson, Brendan O'Connor, Jeffrey Flanigan et al.
17. **[CMUQ-Hybrid: Sentiment Classification By Feature Engineering and Parameter Tuning ↗](https://aclanthology.org/S14-2028/)**Kamla Al-Mannai, Hanan Alshikhabobakr, Sabih Bin Wasi et al.
18. **[CMUQ@Qatar:Using Rich Lexical Features for Sentiment Analysis on Twitter ↗](https://aclanthology.org/S14-2029/)**Sabih Bin Wasi, Rukhsar Neyaz, Houda Bouamor et al.
19. **[CNRC-TMT: Second Language Writing Assistant System Description ↗](https://aclanthology.org/S14-2030/)**Cyril Goutte, Michel Simard, Marine Carpuat
20. **[COMMIT-P1WP3: A Co-occurrence Based Approach to Aspect-Level Sentiment Analysis ↗](https://aclanthology.org/S14-2032/)**Kim Schouten, Flavius Frasincar, Franciska de Jong
21. **[Citius: A Naive-Bayes Strategy for Sentiment Analysis on English Tweets ↗](https://aclanthology.org/S14-2026/)**Pablo Gamallo, Marcos Garcia
22. **[Columbia NLP: Sentiment Detection of Sentences and Subjective Phrases in Social Media ↗](https://aclanthology.org/S14-2031/)**Sara Rosenthal, Kathy McKeown, Apoorv Agarwal
23. **[Coooolll: A Deep Learning System for Twitter Sentiment Classification ↗](https://aclanthology.org/S14-2033/)**Duyu Tang, Furu Wei, Bing Qin et al.
24. **[Copenhagen-Malmö: Tree Approximations of Semantic Parsing Problems ↗](https://aclanthology.org/S14-2034/)**Natalie Schluter, Anders Søgaard, Jakob Elming et al.
25. **[DAEDALUS at SemEval-2014 Task 9: Comparing Approaches for Sentiment Analysis in Twitter ↗](https://aclanthology.org/S14-2035/)**Julio Villena-Román, Janine García-Morera, José Carlos González-Cristóbal
26. **[DCU: Aspect-based Polarity Classification for SemEval Task 4 ↗](https://aclanthology.org/S14-2036/)**Joachim Wagner, Piyush Arora, Santiago Cortes et al.
27. **[DIT: Summarisation and Semantic Expansion in Evaluating Semantic Similarity ↗](https://aclanthology.org/S14-2037/)**Magdalena Kacmajor, John D. Kelleher
28. **[DLIREC: Aspect Term Extraction and Term Polarity Classification System ↗](https://aclanthology.org/S14-2038/)**Zhiqiang Toh, Wenting Wang
29. **[DLS@CU: Sentence Similarity from Word Alignment ↗](https://aclanthology.org/S14-2039/)**Md Arafat Sultan, Steven Bethard, Tamara Sumner
30. **[Duluth : Measuring Cross-Level Semantic Similarity with First and Second Order Dictionary Overlaps ↗](https://aclanthology.org/S14-2040/)**Ted Pedersen
31. **[ECNU: A Combination Method and Multiple Features for Aspect Extraction and Sentiment Polarity Classification ↗](https://aclanthology.org/S14-2041/)**Fangxi Zhang, Zhihua Zhang, Man Lan
32. **[ECNU: Expression- and Message-level Sentiment Orientation Classification in Twitter Using Multiple Effective Features ↗](https://aclanthology.org/S14-2042/)**Jiang Zhao, Man Lan, Tiantian Zhu
33. **[ECNU: Leveraging on Ensemble of Heterogeneous Features and Information Enrichment for Cross Level Semantic Similarity Estimation ↗](https://aclanthology.org/S14-2043/)**Tiantian Zhu, Man Lan
34. **[ECNU: One Stone Two Birds: Ensemble of Heterogenous Measures for Semantic Relatedness and Textual Entailment ↗](https://aclanthology.org/S14-2044/)**Jiang Zhao, Tiantian Zhu, Man Lan
35. **[FBK-TR: Applying SVM with Multiple Linguistic Features for Cross-Level Semantic Similarity ↗](https://aclanthology.org/S14-2046/)**Ngoc Phuoc An Vo, Tommaso Caselli, Octavian Popescu
36. **[FBK-TR: SVM for Semantic Relatedeness and Corpus Patterns for RTE](https://md.research.elamur.ai/free/en/papers/vo-2014-fbk-tr-svm-semantic-relatedeness/)**Ngoc Phuoc An Vo, Octavian Popescu, Tommaso Caselli*our summary*
37. **[GPLSI: Supervised Sentiment Analysis in Twitter using Skipgrams ↗](https://aclanthology.org/S14-2048/)**Javi Fernández, Yoan Gutiérrez, Jose Manuel Gómez et al.
38. **[HulTech: A General Purpose System for Cross-Level Semantic Similarity based on Anchor Web Counts ↗](https://aclanthology.org/S14-2050/)**Jose G. Moreno, Rumen Moraliyski, Asma Berrezoug et al.
39. **[IHS R&D Belarus: Cross-domain extraction of product features using CRF ↗](https://aclanthology.org/S14-2051/)**Maryna Chernyshevich
40. **[IITP: A Supervised Approach for Disorder Mention Detection and Disambiguation ↗](https://aclanthology.org/S14-2052/)**Utpal Kumar Sikdar, Asif Ekbal, Sriparna Saha
41. **[IITP: Supervised Machine Learning for Aspect based Sentiment Analysis ↗](https://aclanthology.org/S14-2053/)**Deepak Kumar Gupta, Asif Ekbal
42. **[IITPatna: Supervised Approach for Sentiment Analysis in Twitter ↗](https://aclanthology.org/S14-2054/)**Raja Selvarajan, Asif Ekbal
43. **[INSIGHT Galway: Syntactic and Lexical Features for Aspect Based Sentiment Analysis ↗](https://aclanthology.org/S14-2058/)**Sapna Negi, Paul Buitelaar
44. **[IUCL: Combining Information Sources for SemEval Task 5 ↗](https://aclanthology.org/S14-2060/)**Alex Rudnick, Levi King, Can Liu et al.
45. **[Illinois-LH: A Denotational and Distributional Approach to Semantics ↗](https://aclanthology.org/S14-2055/)**Alice Lai, Julia Hockenmaier
46. **[In-House: An Ensemble of Pre-Existing Off-the-Shelf Parsers ↗](https://aclanthology.org/S14-2056/)**Yusuke Miyao, Stephan Oepen, Daniel Zeman
47. **[Indian Institute of Technology-Patna: Sentiment Analysis in Twitter ↗](https://aclanthology.org/S14-2057/)**Vikram Singh, Arif Md. Khan, Asif Ekbal
48. **[IxaMed: Applying Freeling and a Perceptron Sequential Tagger at the Shared Task on Analyzing Clinical Texts ↗](https://aclanthology.org/S14-2061/)**Koldo Gojenola, Maite Oronoz, Alicia Pérez et al.
49. **[JOINT_FORCES: Unite Competing Sentiment Classifiers with Random Forest ↗](https://aclanthology.org/S14-2062/)**Oliver Dürr, Fatih Uzdilli, Mark Cieliebak
50. **[JU-Evora: A Graph Based Cross-Level Semantic Similarity Analysis using Discourse Information ↗](https://aclanthology.org/S14-2064/)**Swarnendu Ghosh, Nibaran Das, Teresa Gonçalves et al.
51. **[JU_CSE: A Conditional Random Field (CRF) Based Approach to Aspect Based Sentiment Analysis ↗](https://aclanthology.org/S14-2063/)**Braja Gopal Patra, Soumik Mandal, Dipankar Das et al.
52. **[KUL-Eval: A Combinatory Categorial Grammar Approach for Improving Semantic Parsing of Robot Commands using Spatial Context ↗](https://aclanthology.org/S14-2066/)**Willem Mattelaer, Mathias Verbeke, Davide Nitti
53. **[KUNLPLab:Sentiment Analysis on Twitter Data ↗](https://aclanthology.org/S14-2067/)**Beakal Gizachew Assefa
54. **[Kea: Sentiment Analysis of Phrases Within Short Texts ↗](https://aclanthology.org/S14-2065/)**Ameeta Agrawal, Aijun An
55. **[LIPN: Introducing a new Geographical Context Similarity Measure and a Statistical Similarity Measure based on the Bhattacharyya coefficient ↗](https://aclanthology.org/S14-2069/)**Davide Buscaldi, Jorge García Flores, Joseph Le Roux et al.
56. **[LT3: Sentiment Classification in User-Generated Content Using a Rich Feature Set ↗](https://aclanthology.org/S14-2070/)**Cynthia Van Hee, Marjan Van de Kauter, Orphée De Clercq et al.
57. **[Linköping: Cubic-Time Graph Parsing with a Simple Scoring Scheme ↗](https://aclanthology.org/S14-2068/)**Marco Kuhlmann
58. **[LyS: Porting a Twitter Sentiment Analysis Approach from Spanish to English ↗](https://aclanthology.org/S14-2071/)**David Vilares, Miguel Hermo, Miguel A. Alonso et al.
59. **[Meerkat Mafia: Multilingual and Cross-Level Semantic Textual Similarity Systems ↗](https://aclanthology.org/S14-2072/)**Abhay Kashyap, Lushan Han, Roberto Yus et al.
60. **[MindLab-UNAL: Comparing Metamap and T-mapper for Medical Concept Extraction in SemEval 2014 Task 7 ↗](https://aclanthology.org/S14-2073/)**Alejandro Riveros, Maria De-Arteaga, Fabio González et al.
61. **[NILC_USP: An Improved Hybrid System for Sentiment Analysis in Twitter Messages ↗](https://aclanthology.org/S14-2074/)**Pedro Balage Filho, Lucas Avanço, Thiago Pardo et al.
62. **[NILC_USP: Aspect Extraction using Semantic Labels ↗](https://aclanthology.org/S14-2075/)**Pedro Balage Filho, Thiago Pardo
63. **[NRC-Canada-2014: Detecting Aspects and Sentiment in Customer Reviews](https://md.research.elamur.ai/free/en/papers/kiritchenko-2014-nrc-canada-2014-detecting-aspects/)**Svetlana Kiritchenko, Xiaodan Zhu, Colin Cherry et al.*our summary*
64. **[NRC-Canada-2014: Recent Improvements in the Sentiment Analysis of Tweets ↗](https://aclanthology.org/S14-2077/)**Xiaodan Zhu, Svetlana Kiritchenko, Saif Mohammad
65. **[NTNU: Measuring Semantic Similarity with Sublexical Feature Representations and Soft Cardinality ↗](https://aclanthology.org/S14-2078/)**André Lynum, Partha Pakray, Björn Gambäck et al.
66. **[OPI: Semeval-2014 Task 3 System Description ↗](https://aclanthology.org/S14-2079/)**Marek Kozlowski
67. **[Peking: Profiling Syntactic Tree Parsing Techniques for Semantic Graph Parsing ↗](https://aclanthology.org/S14-2080/)**Yantao Du, Fan Zhang, Weiwei Sun et al.
68. **[Potsdam: Semantic Dependency Parsing by Bidirectional Graph-Tree Transformations and Syntactic Parsing ↗](https://aclanthology.org/S14-2081/)**Željko Agić, Alexander Koller
69. **[Priberam: A Turbo Semantic Parser with Second Order Features ↗](https://aclanthology.org/S14-2082/)**André F. T. Martins, Mariana S. C. Almeida
70. **[RTM-DCU: Referential Translation Machines for Semantic Similarity ↗](https://aclanthology.org/S14-2085/)**Ergun Biçici, Andy Way
71. **[RTRGO: Enhancing the GU-MLT-LT System for Sentiment Analysis of Short Messages ↗](https://aclanthology.org/S14-2086/)**Tobias Günther, Jean Vancoppenolle, Richard Johansson
72. **[RelAgent: Entity Detection and Normalization for Diseases in Clinical Records: a Linguistically Driven Approach ↗](https://aclanthology.org/S14-2083/)**Sv Ramanan, Senthil Nathan
73. **[RoBox: CCG with Structured Perceptron for Supervised Semantic Parsing of Robotic Spatial Commands ↗](https://aclanthology.org/S14-2084/)**Kilian Evang, Johan Bos
74. **[SA-UZH: Verb-based Sentiment Analysis ↗](https://aclanthology.org/S14-2087/)**Nora Hollenstein, Michael Amsler, Martina Bachmann et al.
75. **[SAIL-GRS: Grammar Induction for Spoken Dialogue Systems using CF-IRF Rule Similarity ↗](https://aclanthology.org/S14-2088/)**Kalliopi Zervanou, Nikolaos Malandrakis, Shrikanth Narayanan
76. **[SAIL: Sentiment Analysis using Semantic Similarity and Contrast Features ↗](https://aclanthology.org/S14-2089/)**Nikolaos Malandrakis, Michael Falcone, Colin Vaz et al.
77. **[SAP-RI: A Constrained and Supervised Approach for Aspect-Based Sentiment Analysis ↗](https://aclanthology.org/S14-2090/)**Naveen Nandan, Daniel Dahlmeier, Akriti Vij et al.
78. **[SAP-RI: Twitter Sentiment Analysis in Two Days ↗](https://aclanthology.org/S14-2091/)**Akriti Vij, Nishta Malhotra, Naveen Nandan et al.
79. **[SINAI: Voting System for Aspect Based Sentiment Analysis ↗](https://aclanthology.org/S14-2099/)**Salud María Jiménez-Zafra, Eugenio Martínez-Cámara, Maite Martin et al.
80. **[SINAI: Voting System for Twitter Sentiment Analysis ↗](https://aclanthology.org/S14-2100/)**Eugenio Martínez-Cámara, Salud María Jiménez-Zafra, Maite Martin et al.
81. **[SNAP: A Multi-Stage XML-Pipeline for Aspect Based Sentiment Analysis ↗](https://aclanthology.org/S14-2101/)**Clemens Schulze Wettendorf, Robin Jegan, Allan Körner et al.
82. **[SSMT:A Machine Translation Evaluation View To Paragraph-to-Sentence Semantic Similarity ↗](https://aclanthology.org/S14-2102/)**Pingping Huang, Baobao Chang
83. **[SU-FMI: System Description for SemEval-2014 Task 9 on Sentiment Analysis in Twitter ↗](https://aclanthology.org/S14-2103/)**Boris Velichkov, Borislav Kapukaranov, Ivan Grozev et al.
84. **[SZTE-NLP: Aspect level opinion mining exploiting syntactic cues ↗](https://aclanthology.org/S14-2107/)**Viktor Hangya, Gábor Berend, István Varga et al.
85. **[SZTE-NLP: Clinical Text Analysis with Named Entity Recognition ↗](https://aclanthology.org/S14-2108/)**Melinda Katona, Richárd Farkas
86. **[SeemGo: Conditional Random Fields Labeling and Maximum Entropy Classification for Aspect Based Sentiment Analysis ↗](https://aclanthology.org/S14-2092/)**Pengfei Liu, Helen Meng
87. **[SemEval 2014 Task 5 - L2 Writing Assistant ↗](https://aclanthology.org/S14-2005/)**Maarten van Gompel, Iris Hendrickx, Antal van den Bosch et al.
88. **[SemEval 2014 Task 8: Broad-Coverage Semantic Dependency Parsing ↗](https://aclanthology.org/S14-2008/)**Stephan Oepen, Marco Kuhlmann, Yusuke Miyao et al.
89. **[SemEval-2014 Task 10: Multilingual Semantic Textual Similarity](https://md.research.elamur.ai/free/en/papers/agirre-2014-semeval-2014-task-10-multilingual/)**Eneko Agirre, Carmen Banea, Claire Cardie et al.*our summary*
90. **[SemEval-2014 Task 1: Evaluation of Compositional Distributional Semantic Models on Full Sentences through Semantic Relatedness and Textual Entailment](https://md.research.elamur.ai/free/en/papers/marelli-2014-semeval-2014-task-1-evaluation/)**Marco Marelli, Luisa Bentivogli, Marco Baroni et al.*our summary*
91. **[SemEval-2014 Task 2: Grammar Induction for Spoken Dialogue Systems ↗](https://aclanthology.org/S14-2002/)**Ioannis Klasinas, Elias Iosif, Katerina Louka et al.
92. **[SemEval-2014 Task 3: Cross-Level Semantic Similarity ↗](https://aclanthology.org/S14-2003/)**David Jurgens, Mohammad Taher Pilehvar, Roberto Navigli
93. **[SemEval-2014 Task 4: Aspect Based Sentiment Analysis](https://md.research.elamur.ai/free/en/papers/pontiki-2014-semeval-2014-task-4-aspect/)**Maria Pontiki, Dimitris Galanis, John Pavlopoulos et al.*our summary*
94. **[SemEval-2014 Task 6: Supervised Semantic Parsing of Robotic Spatial Commands ↗](https://aclanthology.org/S14-2006/)**Kais Dukes
95. **[SemEval-2014 Task 7: Analysis of Clinical Text ↗](https://aclanthology.org/S14-2007/)**Sameer Pradhan, Noémie Elhadad, Wendy Chapman et al.
96. **[SemEval-2014 Task 9: Sentiment Analysis in Twitter](https://md.research.elamur.ai/free/en/papers/rosenthal-2014-semeval-2014-task-9-sentiment/)**Sara Rosenthal, Alan Ritter, Preslav Nakov et al.*our summary*
97. **[SemantiKLUE: Robust Semantic Similarity at Multiple Levels Using Maximum Weight Matching ↗](https://aclanthology.org/S14-2093/)**Thomas Proisl, Stefan Evert, Paul Greiner et al.
98. **[Sensible: L2 Translation Assistance by Emulating the Manual Post-Editing Process ↗](https://aclanthology.org/S14-2094/)**Liling Tan, Anne-Kathrin Schumann, Jose M.M. Martinez et al.
99. **[Senti.ue: Tweet Overall Sentiment Classification Approach for SemEval-2014 Task 9 ↗](https://aclanthology.org/S14-2095/)**José Saias
100. **[SentiKLUE: Updating a Polarity Classifier in 48 Hours ↗](https://aclanthology.org/S14-2096/)**Stefan Evert, Thomas Proisl, Paul Greiner et al.

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