Norms of valence, arousal, and dominance for 13,915 English lemmas

The Measurement of Meaning

Osgood, C. E., Suci, G. J., & Tannenbaum, P. H. (1957) · Cited by 9,433

A power primer.

Cohen, J. (1992) · Psychological Bulletin · doi:10.1037//0033-2909.112.1.155 · Cited by 8,771

A solution to Plato's problem: The latent semantic analysis theory of acquisition, induction, and representation of knowledge.

Landauer, T. K., & Dumais, S. T. (1997) · Psychological Review · doi:10.1037/0033-295x.104.2.211 · Cited by 6,282

Sentiment Analysis and Opinion Mining

Zhang, L., & Liu, B. (2017) · Springer eBooks · doi:10.1007/978-1-4899-7687-1_907 · Cited by 3,307

Moving beyond Kučera and Francis: A critical evaluation of current word frequency norms and the introduction of a new and improved word frequency measure for American English

Brysbaert, M., & New, B. (2009) · Behavior Research Methods · doi:10.3758/brm.41.4.977 · Cited by 2,821

The English Lexicon Project

Balota, D. A., Yap, M. J.-M., Hutchison, K. A., Cortese, M. J., Kessler, B., Loftis, B., Neely, J. H., Nelson, D. L., Simpson, G. B., & Rebecca Treiman, A. (2007) · Behavior Research Methods · doi:10.3758/bf03193014 · Cited by 2,758

Sentiment Analysis and Opinion Mining

Liu, B. (2012) · Synthesis lectures on human language technologies · doi:10.1007/978-3-031-02145-9 · Cited by 1,872

Age-of-acquisition ratings for 30,000 English words

Kuperman, V., Stadthagen-González, H., & Brysbaert, M. (2012) · Behavior Research Methods · doi:10.3758/s13428-012-0210-4 · Cited by 1,308

The representation of abstract words: Why emotion matters.

Kousta, S. T., Vigliocco, G., Vinson, D., Andrews, M. W., & Campo, E. D. (2010) · Journal of Experimental Psychology General · doi:10.1037/a0021446 · Cited by 958

A meta-analytic review of research on gender differences in sexuality, 1993–2007.

Petersen, J. L., & Hyde, J. S. (2010) · Psychological Bulletin · doi:10.1037/a0017504 · Cited by 931

Image Recoloring with Valence‐Arousal Emotion Model

Kim, H., Kang, H., & Lee, I. (2016) · Computer Graphics Forum · doi:10.1111/cgf.13018 · Cited by 18

Five Shades of Untruth: Finer-Grained Classification of Fake News

Wang, L., Wang, Y., de Melo, G., & Weikum, G. (2018) · IEEE/ACM International Conference on Advances in Social Networks Analysis and Mining (ASONAM) · doi:10.1109/asonam.2018.8508256 · Cited by 18

Contextual cues as modifiers of cTBS effects on indulgent eating

Safati, A. B., & Hall, P. A. (2019) · Brain stimulation · doi:10.1016/j.brs.2019.05.003 · Cited by 18

Understanding archetypes of fake news via fine-grained classification

Wang, L., Wang, Y., de Melo, G., & Weikum, G. (2019) · Social Network Analysis and Mining · doi:10.1007/s13278-019-0580-z · Cited by 18

Keep calm and carry on: electrophysiological evaluation of emotional anticipation in the second language

Jończyk, R., Korolczuk, I., Balatsou, E., & Thierry, G. (2019) · Social Cognitive and Affective Neuroscience · doi:10.1093/scan/nsz066 · Cited by 20

M-Hair: Creating Novel Tactile Feedback by Augmenting the Body Hair to Respond to Magnetic Field

Boldú, R., Jain, S., Cortés, J. P. F., Zhang, H., & Nanayakkara, S. C. (2019) · ACM Symposium on User Interface Software and Technology (UIST) · doi:10.1145/3332165.3347955 · Cited by 18

Joint emotion label space modeling for affect lexica

Bruyne, L. D., Atanasova, P., & Augenstein, I. (2021) · Computer Speech & Language · doi:10.1016/j.csl.2021.101257 · Cited by 26

Individual Differences in Print Exposure Predict Use of Implicit Causality in Pronoun Comprehension and Referential Prediction

Johnson, E., & Arnold, J. E. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.672109 · Cited by 19

Understanding Miscommunication: Speech Act Recognition in Digital Contexts

Holtgraves, T. (2021) · Cognitive Science · doi:10.1111/cogs.13023 · Cited by 18

Cryptocurrency ecosystems and social media environments: An empirical analysis through Hawkes’ models and natural language processing

Ortu, M., Vacca, S., Destefanis, G., & Conversano, C. (2021) · Machine Learning with Applications · doi:10.1016/j.mlwa.2021.100229 · Cited by 18

TERMS: textual emotion recognition in multidimensional space

Ghafoor, Y., Jinping, S., Calderón, F., Huang, Y.-H., Chen, K.-T., & Chen, Y.-S. (2022) · Applied Intelligence · doi:10.1007/s10489-022-03567-4 · Cited by 18

A Benchmark Comparison of State-of-the-Practice Sentiment Analysis Methods.Preprint

Ribeiro, F. N., Araújo, M., Gonçalves, P., Benevenuto, F., & Gonçalves, M. A. (2015) · arXiv (Cornell University) · Cited by 18

Emotion from the sound of a word: Statistical relationships between surface form and valence of English words influence lexical access and memory.

de Zubicaray, G. I., McMahon, K. L., Arciuli, J., Kearney, E., & Guenther, F. H. (2023) · Journal of Experimental Psychology General · doi:10.1037/xge0001477 · Cited by 18

DerLex: An eye-movement database of derived word reading in English

Schmidtke, D., Dyke, J. A. V., & Kuperman, V. (2024) · Behavior Research Methods · doi:10.3758/s13428-024-02565-3 · Cited by 17

From Abstract Symbols to Emotional (In-)Sights: An Eye Tracking Study on the Effects of Emotional Vignettes and Pictures

Usée, F., Jacobs, A. M., & Lüdtke, J. (2020) · Frontiers in Psychology · doi:10.3389/fpsyg.2020.00905 · Cited by 25

Age-Related Differences in Affective Norms for Chinese Words (AANC)

Liu, P., Lu, Q., Zhang, Z., Tang, J., & Han, B. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.585666 · Cited by 17

Subtle Contact Nuances in the Delivery of Human-to-Human Touch Distinguish Emotional Sentiment

Xu, S., Xu, C., McIntyre, S., Olausson, H., & Gerling, G. J. (2021) · IEEE Transactions on Haptics · doi:10.1109/toh.2021.3137833 · Cited by 18

Negative comments and social media: How cognitive biases relate to body image concerns

Dent, E., & Martin, A. K. (2023) · Body Image · doi:10.1016/j.bodyim.2023.01.008 · Cited by 22

Quantifying Valence and Arousal in Text with Multilingual Pre-trained Transformers

Mendes, G. A., & Martins, B. (2023) · Lecture notes in computer science · doi:10.1007/978-3-031-28244-7_6 · Cited by 24

Brain potentials reveal how emotion filters native language access when bilinguals read words in their second language

Zhang, W., Jończyk, R., Wu, Y. J., Lan, Y., Gao, Z., Hu, J., Thierry, G., & Gao, S. (2023) · Cerebral Cortex · doi:10.1093/cercor/bhad161 · Cited by 21

Linguistic and emotional-valence characteristics of reading passages for clinical use and research

Ben‐David, B. M., Moral, M. I., Namasivayam, A. K., Erel, H., & Lieshout, P. H. H. M. V. (2016) · Journal of Fluency Disorders · doi:10.1016/j.jfludis.2016.06.003 · Cited by 17

System for matching paintings with music based on emotions

Lee, T., Lim, H., Kim, D., Hwang, S.-K., & Yoon, K. (2016) · SIGGRAPH Asia Technical Briefs · doi:10.1145/3005358.3005366 · Cited by 17

The Effect of Memory in Inducing Pleasant Emotions with Musical and Pictorial Stimuli

Maksimainen, J. P., Wikgren, J., Eerola, T., & Saarikallio, S. H. (2018) · Scientific Reports · doi:10.1038/s41598-018-35899-y · Cited by 19

The Key Practice, Building and Sharing Stories and Social Understandings: The Intrinsic Value of Narrative

Deane, P., Somasundaran, S., Lawless, R. R., Persky, H., & Appel, C. (2019) · ETS Research Report Series · doi:10.1002/ets2.12266 · Cited by 21

Getting a (big) data-based grip on ideological change. Evidence from Belgian Dutch

Grondelaers, S., Speelman, D., Lybaert, C., & van Gent, P. (2020) · Journal of Linguistic Geography · doi:10.1017/jlg.2020.2 · Cited by 17

The dynamics of negative stereotypes as revealed by tweeting behavior in the aftermath of the Charlie Hebdo terrorist attack

Marzouki, Y., Barach, E., Srinivasan, V., Shaikh, S., & Feldman, L. B. (2020) · Heliyon · doi:10.1016/j.heliyon.2020.e04311 · Cited by 17

Structured Self-Attention Weights Encode Semantics in Sentiment Analysis

Wu, Z., Nguyen, T.-S., & Ong, D. C. (2020) · BlackboxNLP Workshop on Analyzing and Interpreting Neural Networks for NLP (BlackboxNLP) · doi:10.18653/v1/2020.blackboxnlp-1.24 · Cited by 21

Animate and Inanimate Words Demonstrate Equivalent Retrieval Dynamics Despite the Occurrence of the Animacy Advantage

Serra, M. J. (2021) · Frontiers in Psychology · doi:10.3389/fpsyg.2021.661451 · Cited by 17

Abnormal evidence accumulation underlies the positive memory deficit in depression.

Cataldo, A. M., Scheuer, L., Maksimovskiy, A. L., Germine, L. T., & Dillon, D. G. (2022) · Journal of Experimental Psychology General · doi:10.1037/xge0001268 · Cited by 17

Reliability of the sliding scale for collecting affective responses to words

Imbault, C., Shore, D. I., & Kuperman, V. (2018) · Behavior Research Methods · doi:10.3758/s13428-018-1016-9 · Cited by 17

Contextual Characteristics of Concrete and Abstract Words.

Frassinelli, D., Naumann, D., Utt, J., & Walde, S. S. I. (2017) · Cited by 17

When the filter bubble bursts

Abisheva, A., García, D., & Schweitzer, F. (2016) · ACM Web Science Conference (WebSci) · doi:10.1145/2908131.2908180 · Cited by 17

Valence does not affect serial recall.

Bireta, T. J., Guitard, D., Neath, I., & Surprenant, A. M. (2021) · Canadian Journal of Experimental Psychology/Revue canadienne de psychologie expérimentale · doi:10.1037/cep0000239 · Cited by 17

The Effect of Heterogeneous Data for Alzheimer's Disease Detection from SpeechPreprint

Balagopalan, A., Novikova, J., Rudzicz, F., & Ghassemi, M. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1811.12254 · Cited by 18

Deep Feelings: A Massive Cross-Lingual Study on the Relation between Emotions and ViralityPreprint

Guerini, M., & Staiano, J. (2015) · arXiv (Cornell University) · doi:10.48550/arxiv.1503.04723 · Cited by 19

Emotional Reactivity and Police Expertise in Use-of-Force Decision-Making

Ta, V. P., Lande, B., & Suss, J. (2021) · Journal of Police and Criminal Psychology · doi:10.1007/s11896-020-09428-5 · Cited by 17

Semantic ambiguity and memory

Brainerd, C. J., Chang, M., Bialer, D. M., & Toglia, M. P. (2021) · Journal of Memory and Language · doi:10.1016/j.jml.2021.104286 · Cited by 19

Automated speech and language markers of longitudinal changes in psychosis symptoms

Tang, S. X., Spilka, M. J., John, M., Birnbaum, M. L., Saito, E., Berretta, S. A., Behbehani, L. M., Liberman, M., Malhotra, A. K., Simpson, W., et al. (2025) · NPP—Digital Psychiatry and Neuroscience · doi:10.1038/s44277-025-00034-z · Cited by 23

The construction of emotional meaning in language

Hoemann, K., Lee, Y., Dussault, È., Devylder, S., Ungar, L., Geeraerts, D., & Mesquita, B. (2025) · Communications Psychology · doi:10.1038/s44271-025-00255-0 · Cited by 38

Modeling the interaction between sensory and affective meanings for detecting metaphor

Gargett, A., & Barnden, J. A. (2015) · Workshop on Metaphor in NLP · doi:10.3115/v1/w15-1403 · Cited by 16

The Role of Linguistic Information in Learning Abstract Words: Evidence from Children with Specific Language Impairment (SLI).

Vigliocco, G., Ponari, M., & Norbury, C. (2017) · eScholarship (California Digital Library) · Cited by 16

“Make it Happen!”

Formanowicz, M., Pietraszkiewicz, A., Roessel, J., Suitner, C., Witkowska, M., & Maass, A. (2021) · Social Psychology · doi:10.1027/1864-9335/a000435 · Cited by 16

Common functional localizers to enhance NHP & cross-species neuroscience imaging research

Russ, B. E., Petkov, C. I., Kwok, S. C., Zhu, Q., Belin, P., Vanduffel, W., & Hamed, S. B. (2021) · NeuroImage · doi:10.1016/j.neuroimage.2021.118203 · Cited by 16

Attention and regulation during emotional word comprehension in older adults: Evidence from event-related potentials and brain oscillations.

Ku, L., Allen, J. J. B., & Lai, V. (2022) · Brain and Language · doi:10.1016/j.bandl.2022.105086 · Cited by 11

Before/after Bayes: A comparison of frequentist and Bayesian mixed‐effects models in applied psychological research

Flores, R. D., Sanders, C. A., Duan, S. X., Bishop-Chrzanowski, B. M., Oyler, D. L., Shim, H.-J., Clocksin, H. E., Miller, A. P., & Merkle, E. C. (2022) · British Journal of Psychology · doi:10.1111/bjop.12585 · Cited by 16

ASR and Emotional Speech: A Word-Level Investigation of the Mutual Impact of Speech and Emotion Recognition

Li, Y., Zhao, Z., Klejch, O., Bell, P., & Lai, C. (2023) · Interspeech (USB) · doi:10.21437/interspeech.2023-2078 · Cited by 20

Acute stress influences the emotional foundations of executive control: Distinct effects on control-related affective and cognitive processes

Shields, G. S., Hunter, C. L., Trudell, E. V., Gray, Z. J., Perkins, B. C., Patterson, E. G., & Zalenski, P. K. (2023) · Psychoneuroendocrinology · doi:10.1016/j.psyneuen.2023.106942 · Cited by 23

Emotions, Demographics and Sociability in Twitter Interactions

Lerman, K., Arora, M., Gallegos, L., Kumaraguru, P., & García, D. (2021) · Proceedings of the International AAAI Conference on Web and Social Media · doi:10.1609/icwsm.v10i1.14728 · Cited by 16

Gender-Distinguishing Features in Film Dialogue

Schofield, A., & Mehr, L. (2016) · Joint SIGHUM Workshop on Computational Linguistics for Cultural Heritage, Social Sciences, Humanities and Literature (LaTeCH-CLfL) · doi:10.18653/v1/w16-0204 · Cited by 20

The behavioral and neural basis of foreign language effect on risk-taking

Zheng, L., Mobbs, D., & Yu, R. (2019) · Neuropsychologia · doi:10.1016/j.neuropsychologia.2019.107290 · Cited by 17

Somatic and visceral effects of word valence, arousal and concreteness in a continuum lexical space

Vergallito, A., Petilli, M. A., Cattaneo, L., & Marelli, M. (2019) · Scientific Reports · doi:10.1038/s41598-019-56382-2 · Cited by 17

On the causal relation between real world activities and emotional expressions of social media users

Falavarjani, S. A. M., Jovanović, J., Fani, H., Ghorbani, A., Noorian, Z., & Bagheri, E. (2020) · J. Assoc. Inf. Sci. Technol. · doi:10.1002/asi.24440 · Cited by 16

Valence-dependent mutation in lexical evolution

Jackson, J. C., Lindquist, K. A., Drabble, R., Atkinson, Q. D., & Watts, J. (2022) · Nature Human Behaviour · doi:10.1038/s41562-022-01483-8 · Cited by 16

Emotional connotations of words related to authority and community

Schauenburg, G., Ambrasat, J., Schröder, T., von Scheve, C., & Conrad, M. (2014) · Behavior Research Methods · doi:10.3758/s13428-014-0494-7 · Cited by 16

The semantics of emotion in false memory.

Brainerd, C. J., & Bookbinder, S. H. (2018) · Emotion · doi:10.1037/emo0000431 · Cited by 16

Pipelined Neural Networks for Phrase-Level Sentiment Intensity Prediction

Yu, L.-C., Wang, J., Lai, K.-H. R., & Zhang, X. (2018) · IEEE Transactions on Affective Computing · doi:10.1109/taffc.2018.2807819 · Cited by 16

Personalized smart home audio system with automatic music selection based on emotion

Kang, D., & Seo, S. (2018) · Multimedia Tools and Applications · doi:10.1007/s11042-018-6733-7 · Cited by 16

Gesture Authentication for Smartphones: Evaluation of Gesture Password Selection Policies

Cheon, E., Shin, Y., Huh, J. H., Kim, H., & Oakley, I. (2020) · IEEE Symposium on Security and Privacy (S&P) · doi:10.1109/sp40000.2020.00034 · Cited by 16

The Resonance of Metaphor: Evidence for Latino Preferences for Metaphor and Analogy

Ondish, P., Cohen, D., Lucas, K. W., & Vandello, J. A. (2019) · Personality and Social Psychology Bulletin · doi:10.1177/0146167219833390 · Cited by 15

Dynamic, Incremental, and Continuous Detection of Cyberbullying in Online Social Media

Chelmis, C., & Zois, D. (2021) · ACM Transactions on the Web · doi:10.1145/3448014 · Cited by 15

Style is NOT a single variable: Case Studies for Cross-Stylistic Language Understanding

Kang, D., & Hovy, E. H. (2021) · doi:10.18653/v1/2021.acl-long.185 · Cited by 28

Refining Word Embeddings with Sentiment Information for Sentiment Analysis

Kasri, M., Birjali, M., Nabil, M., Beni‐Hssane, A., El-Ansari, A., & Fissaoui, M. E. (2022) · Journal of ICT Standardization · doi:10.13052/jicts2245-800x.1031 · Cited by 17

VAD-assisted multitask transformer framework for emotion recognition and intensity prediction on suicide notes

Ghosh, S. K., Ekbal, A., & Bhattacharyya, P. (2022) · Information Processing & Management · doi:10.1016/j.ipm.2022.103234 · Cited by 16

Predicting implicit attitudes with natural language data

Bhatia, S., & Walasek, L. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2220726120 · Cited by 15

The bright side of words: Norms for 9000 Spanish words in seven discrete positive emotions

Hinojosa, J. A., Guasch, M., Montoro, P. R., Albert, J., Fraga, I., & Ferré, P. (2023) · Behavior Research Methods · doi:10.3758/s13428-023-02229-8 · Cited by 17

Business-to-Investor Marketing: The Interplay of Costly and Costless Signals

Nyilasy, G., Yi, S., Herhausen, D., Ludwig, S., & Dahl, D. W. (2024) · Journal of Marketing · doi:10.1177/00222429241288464 · Cited by 15

A Rose by Another Name? Odor Misnaming is Associated with Linguistic Properties

Hörberg, T., Kurfalı, M., Larsson, M. U., Laukka, E. J., Herman, P. A., & Olofsson, J. (2024) · Cognitive Science · doi:10.1111/cogs.70003 · Cited by 15

Affective Lexicon Creation for the Greek Language

Palogiannidi, E., Koutsakis, P., Iosif, E., & Potamianos, A. (2016) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/3zni3fqskjg7 · Cited by 15

The Affective Norms for Polish Short Texts (ANPST) Database Properties and Impact of Participants’ Population and Sex on Affective Ratings

Imbir, K. K. (2017) · Frontiers in Psychology · doi:10.3389/fpsyg.2017.00855 · Cited by 15

Evaluation of the Relationship Between Virtual Environments and Emotions

Oliveira, T., Noriega, P., Rebelo, F., & Heidrich, R. D. O. (2017) · Advances in intelligent systems and computing · doi:10.1007/978-3-319-60582-1_8 · Cited by 18

Feasible Annotation Scheme for Capturing Policy Argument Reasoning using Argument Templates

Reisert, P., Inoue, N., Kuribayashi, T., & Inui, K. (2018) · Workshop on Argument Mining (ArgMining) · doi:10.18653/v1/w18-5210 · Cited by 15

Expressiveness Influences Human Vocal Alignment Toward voice-AI

Cohn, M., & Zellou, G. (2019) · Interspeech (USB) · doi:10.21437/interspeech.2019-1368 · Cited by 15

The Semantic Organization of the English Odor Vocabulary

Hörberg, T., Larsson, M. U., & Olofsson, J. (2022) · Cognitive Science · doi:10.1111/cogs.13205 · Cited by 25

Identifying Leadership Characteristics from Social Media Data during Natural Hazards using Personality Traits

Agarwal, A., & Toshniwal, D. (2020) · Scientific Reports · doi:10.1038/s41598-020-59086-0 · Cited by 15

Visual features influence thought content in the absence of overt semantic information

Schertz, K. E., Kardan, O., & Berman, M. G. (2020) · Attention Perception & Psychophysics · doi:10.3758/s13414-020-02121-z · Cited by 16

Emotional intelligence, working memory, and emotional vocabulary in L1 and L2: Interactions and dissociations

Mavrou, I. (2021) · Lingua · doi:10.1016/j.lingua.2021.103083 · Cited by 17

Independent effects of collocation strength and contextual predictability on eye movements in reading

Li, H., Warrington, K. L., Pagán, A., Paterson, K. B., & Wang, X. (2021) · Language Cognition and Neuroscience · doi:10.1080/23273798.2021.1922726 · Cited by 15

Relating emotional variables to recognition memory performance: a large-scale re-analysis of megastudy data

Cortese, M. J., & Khanna, M. M. (2022) · Memory · doi:10.1080/09658211.2022.2055080 · Cited by 15

Reward-Penalty Weighted Ensemble for Emotion State Classification from Multi-Modal Data Streams

Nandi, A., Xhafa, F., Subirats, L., & Fort, S. (2022) · International Journal of Neural Systems · doi:10.1142/s0129065722500496 · Cited by 15

Happy Accident: A Sentiment Composition Lexicon for Opposing Polarity Phrases

Kiritchenko, S., & Mohammad, S. M. (2016) · Language Resources and Evaluation Conference (LREC) · doi:10.63317/4t4dos9nfuyi · Cited by 15

Does putting your emotions into words make you feel better? Measuring the minute-scale dynamics of emotions from online dataPreprint

Fan, R., Varamesh, A., Varol, O., Barron, A., van de Leemput, I. A., Scheffer, M., & Bollen, J. (2018) · arXiv (Cornell University) · doi:10.48550/arxiv.1807.09725 · Cited by 15

The interplay between language and emotion: a narrative review

Ferré, P., Fraga, I., & Hinojosa, J. A. (2025) · Cognition & Emotion · doi:10.1080/02699931.2025.2549965 · Cited by 23

Connected speech markers of amyloid burden in primary progressive aphasia

Slegers, A., Chafouleas, G., Montembeault, M., Bedetti, C., Welch, A. E., Rabinovici, G. D., Langlais, P., Gorno‐Tempini, M. L., & Brambati, S. M. (2021) · Cortex · doi:10.1016/j.cortex.2021.09.010 · Cited by 16

The language of happiness in self-reported descriptions of happy moments: Words, concepts, and entities

Ortiz, A. M., Hernández, C. P., & García-Gámez, M. (2022) · Humanities and Social Sciences Communications · doi:10.1057/s41599-022-01202-8 · Cited by 16

Detection of EEG Patterns for Induced Fear Emotion State via EMOTIV EEG Testbench

GÜMÜŞ, A. E., Uyulan, Ç., & Güleken, Z. (2022) · Natural and Engineering Sciences · doi:10.28978/nesciences.1159248 · Cited by 14

Socialness effects in lexical–semantic processing.

Diveica, V., Muraki, E. J., Binney, R. J., & Pexman, P. M. (2024) · Journal of Experimental Psychology Learning Memory and Cognition · doi:10.1037/xlm0001328 · Cited by 18

Valence without meaning: Investigating form and semantic components in pseudowords valence

Gatti, D., Raveling, L., Petrenco, A., & Günther, F. (2024) · Psychonomic Bulletin & Review · doi:10.3758/s13423-024-02487-3 · Cited by 14

Neural correlates of emotion-label vs. emotion-laden word processing in late bilinguals: evidence from an ERP study

Tang, D., Li, X., Fu, Y., Wang, H., Li, X., Parviainen, T. M., & Kärkkäinen, T. (2024) · Cognition & Emotion · doi:10.1080/02699931.2024.2352584 · Cited by 14

Decoding the essence of two-character Chinese words: Unveiling valence, arousal, concreteness, familiarity, and imageability through word norming

Chan, Y., & Tse, C. (2024) · Behavior Research Methods · doi:10.3758/s13428-024-02437-w · Cited by 14

Skin conductance response and habituation to emotional facial expressions and words

Juuse, L., Tamm, D., Lõo, K., Allïk, J., & Kreegipuu, K. (2024) · Acta Psychologica · doi:10.1016/j.actpsy.2024.104573 · Cited by 17

Perception of valence and arousal in German emotion terms: A comparison between 9-year-old children and adults

Bahn, D., Kauschke, C., Vesker, M., & Schwarzer, G. (2017) · Applied Psycholinguistics · doi:10.1017/s0142716417000443 · Cited by 14

National character stereotypes mirror language use: A study of Canadian and American tweets

Snefjella, B., Schmidtke, D., & Kuperman, V. (2018) · PLoS ONE · doi:10.1371/journal.pone.0206188 · Cited by 16

Prior Emotional Context Modulates Early Event-Related Potentials to Neutral Retrieval Cues

Bowen, H. J., Fields, E. C., & Kensinger, E. A. (2019) · Journal of Cognitive Neuroscience · doi:10.1162/jocn_a_01451 · Cited by 14

Building the perfect curse word: A psycholinguistic investigation of the form and meaning of taboo words

Reilly, J. J., Kelly, A. E., Zuckerman, B. M., Twigg, P., Wells, M., Jobson, K. R., & Flurie, M. (2020) · Psychonomic Bulletin & Review · doi:10.3758/s13423-019-01685-8 · Cited by 14

Inferior parietal lobule is sensitive to different semantic similarity relations for concrete and abstract words

Montefinese, M., Pinti, P., Ambrosini, E., Tachtsidis, I., & Vinson, D. (2020) · Psychophysiology · doi:10.1111/psyp.13750 · Cited by 14

Affect across adulthood: Evidence from English, Dutch, and Spanish.

Kyröläinen, A.-J., Keuleers, E., Mandera, P., Brysbaert, M., & Kuperman, V. (2021) · Journal of Experimental Psychology General · doi:10.1037/xge0000950 · Cited by 15

Bigram semantic distance as an index of continuous semantic flow in natural language: Theory, tools, and applications.

Reilly, J. J., Finley, A. M., Litovsky, C. P., & Kenett, Y. N. (2023) · Journal of Experimental Psychology General · doi:10.1037/xge0001389 · Cited by 15

Intend to analyze Social Media feeds to detect behavioral trends of individuals to proactively act against Social Threats

Jindal, S., & Sharma, K. (2018) · Procedia Computer Science · doi:10.1016/j.procs.2018.05.191 · Cited by 14

Retrieval practice improves item memory but not source memory in the context of stress

Smith, A. M., Race, E., Davis, F. C., & Thomas, A. K. (2018) · Brain and Cognition · doi:10.1016/j.bandc.2018.12.005 · Cited by 14

Neurophysiological Effects Associated With Subliminal Conditioning of Appetite Motivations

Amd, M., & Baillet, S. (2019) · Frontiers in Psychology · doi:10.3389/fpsyg.2019.00457 · Cited by 14

Reproducing affective norms with lexical co-occurrence statistics: Predicting valence, arousal, and dominance

Recchia, G. L., & Louwerse, M. M. (2014) · Quarterly Journal of Experimental Psychology · doi:10.1080/17470218.2014.941296 · Cited by 84

Norms of valence, arousal, dominance, and age of acquisition for 4,300 Dutch words

Moors, A., Houwer, J. D., Hermans, D., Wanmaker, S., van Schie, K., van Harmelen, A., Schryver, M. D., Winne, J. D., & Brysbaert, M. (2012) · Behavior Research Methods · doi:10.3758/s13428-012-0243-8 · Cited by 326

Norms of valence and arousal for 14,031 Spanish words

Stadthagen-González, H., Imbault, C., Sánchez, M. Á. P., & Brysbaert, M. (2016) · Behavior Research Methods · doi:10.3758/s13428-015-0700-2 · Cited by 237

Characterization of the Affective Norms for English Words by discrete emotional categories

Stevenson, R. A., Mikels, J. A., & James, T. W. (2007) · Behavior Research Methods · doi:10.3758/bf03192999 · Cited by 252

Validation of the Affective Norms for English Words (ANEW) as Weighted Computerized Language Measures of Arousal, Valence and Dominance

Murphy, S. (2014) · Figshare · doi:10.6084/m9.figshare.913449