204 research outputs found
Echoes of Persuasion: The Effect of Euphony in Persuasive Communication
While the effect of various lexical, syntactic, semantic and stylistic
features have been addressed in persuasive language from a computational point
of view, the persuasive effect of phonetics has received little attention. By
modeling a notion of euphony and analyzing four datasets comprising persuasive
and non-persuasive sentences in different domains (political speeches, movie
quotes, slogans and tweets), we explore the impact of sounds on different forms
of persuasiveness. We conduct a series of analyses and prediction experiments
within and across datasets. Our results highlight the positive role of phonetic
devices on persuasion
Exploring Text Virality in Social Networks
This paper aims to shed some light on the concept of virality - especially in
social networks - and to provide new insights on its structure. We argue that:
(a) virality is a phenomenon strictly connected to the nature of the content
being spread, rather than to the influencers who spread it, (b) virality is a
phenomenon with many facets, i.e. under this generic term several different
effects of persuasive communication are comprised and they only partially
overlap. To give ground to our claims, we provide initial experiments in a
machine learning framework to show how various aspects of virality can be
independently predicted according to content features
Ecological Evaluation of Persuasive Messages Using Google AdWords
In recent years there has been a growing interest in crowdsourcing
methodologies to be used in experimental research for NLP tasks. In particular,
evaluation of systems and theories about persuasion is difficult to accommodate
within existing frameworks. In this paper we present a new cheap and fast
methodology that allows fast experiment building and evaluation with
fully-automated analysis at a low cost. The central idea is exploiting existing
commercial tools for advertising on the web, such as Google AdWords, to measure
message impact in an ecological setting. The paper includes a description of
the approach, tips for how to use AdWords for scientific research, and results
of pilot experiments on the impact of affective text variations which confirm
the effectiveness of the approach.Comment: To appear at ACL 2012. 9 pages, 2 figure
Aligning verb senses in two Italian lexical semantic resources
National audienceThis work describes the evaluations of three different approaches, Lexical Match, Sense Similarity based on Personalized Page Rank, and Semantic Match based on Shallow Frame Structures, for word sense alignment of verbs between two Italian lexical-semantic resources, MultiWordNet and the Senso Comune Lexicon. The results obtained are quite satisfying with a final F1 score of 0.47 when merging together Lexical Match and Sense Similarity
Enriching the "Senso Comune" Platform with Automatically Acquired Data
International audienceThis paper reports on research activities on automatic methods for the enrichment of the Senso Comune platform. At this stage of development, we will report on two tasks, namely word sense alignment with MultiWordNet and automatic acquisition of Verb Shallow Frames from sense annotated data in the MultiSemCor corpus. The results obtained are satisfying. We achieved a final F-measure of 0.64 for noun sense alignment and a F-measure of 0.47 for verb sense alignment, and an accuracy of 68% on the acquisition of VerbShallow Frames
Aligning an Italian WordNet with a lexicographic dictionary: Coping with limited data
International audienceThis work describes the evaluations of two approaches, Lexical Matching and Sense Similarity, for word sense alignment between MultiWordNet and a lexicographic dictionary, Senso Comune De Mauro, when having few sense descriptions (MultiWordNet) and no structure over senses (Senso Comune De Mauro). The results obtained from the merging of the two approaches are satisfying, with F1 values of 0.47 for verbs and 0.64 for nouns
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