| Can emotional valence in stories be determined from words? |
Cognitive and Emotion 1994 |
1. Compare the affective tones of the sentences of four texts as perceived by readers, to the values generated by the words that compose the texts. 2. Support the psychological reality of the affective tones of linguistic units larger than a word, and the possibility of their evaluation through the lexical information |
| Exploring the Compositionality of Emotions in Text: Word Emotions, Sentence Emotions and Automated Tagging |
AAAI 2006 |
Presents an approach to automated marking up of texts with emotional labels. |
| Expressing Emotion in Text-based Communication |
CHI 2007 |
1. Examines how people express and detect emotions during text-based communication. 2. Result shows that users relied on four strategies to express happiness versus sadness, including disagreement, negative affect terms, punctuation, and verbosity. |
| Measuring emotional expression with the Linguistic Inquiry and Word Count |
The American Journal of Psychology 2007 |
1. Assess whether the LIWC counts of emotion processes words are sensitive to verbal expression of sadness and amusement. 2. Result shows that LIWC appears to be a valid method for measuring verbal expression of emotion |
| Distributional Semantic Models for Affective Text Analysis |
IEEE TASLP 2013 |
1. Present an affective text analysis model that can directly estimate and combine affective ratings of multi-word terms, with application to the problem of sentence polarity/semantic orientation detection. 2. The affective ratings for n-gram terms of different orders are estimated via a corpus-based method using distributional semantic similarity metrics between unseen words and a set of seed words. |
| EMOTIONS IN TEXT: DIMENSIONAL AND CATEGORICAL MODELS |
CI 2013 |
Introduce a new way of using normative databases as a way of processing text with a dimensional model and compare it with different categorical approaches. |
| The Distribution of Affective Words in a Corpus of Newspaper Articles |
CILC 2013 |
Concerns the distribution of affective words within the various subgenres of a newspaper corpus along three affective parameters: Valence (V), pleasantness, Arousal (A), the intensity of the emotion, and Dominance (D), the degree of control exerted by the perceiver over the stimulus. |
| The emotion potential of simple sentences: additive or interactive effects of nouns and adjectives? |
Frontiers in Psychology 2015 |
1. Assess how the different valences of words in a sentence influence its processing and supralexical affective evaluation. 2. Result shows that sentences with emotionally congruent words (e.g., The grandpa is clever) were verified faster than sentences containing emotionally incongruent words (e.g., The grandpa is lonely. 3. Negative adjectives dominated supralexical evaluation |
| Sentiment Analysis: A review and comparative analysis of web services |
Information Sciences 2015 |
1. Sentiment analysis definition: to analyze people's sentiments, opinions, attitudes, emotions, etc., towards elements such as topics, products, individuals, organizations, and services. 2. Goal of this work: to review and compare 15 free access web services for sentiment analysis, analyzing their capabilities to classify and score different pieces of text with respect to the sentiments contained therein. |
| Identifying Emotions for Social Support Analysis in Online Health Communities |
IJCNLP 2017 |
1. Emotion types recognition in online health communities yields useful information of users' emotional status. 2. High-level features created by CNN without manufacturing any manual or automatic features. 3. Improved accuracy over prior works on identifying emotional messages. 4. Comparison of patients' emotional status between holiday and normal day in USA. |