1,721,125 research outputs found
Going Beyond Counting First Authors in Author Co-citation Analysis
Full text linkThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
Boosting or Attenuating? The Llinguistic Features of Sentiment Strength in User Generated Content
No full textAs markets have been labeled as conversations and consumer-to-consumer communications
have been recognized as a dominant force in driving consumer patronage, companies are facing
the challenge of having to resort to a new generation of performance metrics that provides guidance in a social commerce environment. With respect to this, sentiment analysis of text-based. User Generated Content (UCG) has become an increasingly popular way of staying in touch with customers. The viability of sentiment analysis as a performance metric, however, has been seriously questioned due to its limited predictive ability in assessing diverging degrees of positive and negative sentiments embedded in large and diverse volumes of online textual conversations. In this study, we advance automated text-mining modeling, based on linguistic theory, to deal with aforementioned issues. On the basis of emergent theorizing on speech acts, we zoom in on how linguistic style elements -modal and relational meaning- can boost or attenuate sentiment expression in online customer reviews. The modality of sentiment is accounted for by considering arousal intensity of affect-laden words. Moreover, commonalities of linguistic style elements on the basis of function words, such as pronouns, tenses and word interlinks (patterns) reflect conversants’ alliance or relational closeness to a consensual style of interaction. This is referred to as linguistic style matching. We test our theory-based predictions by examining more than
100.000 reviews across a range of 8 different product/service categories. The empirical results
show that adding aforementioned linguistic elements increases the predictive ability of a sentiment classification model of customer online reviews, allowing firms to develop better quantitative metrics from online textual information. Finally, we corroborate our approach in sampled Facebook and Twitter conversations. Theoretical and managerial implications are discusse
Variations on the Author
Full text link“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
Appropriate Similarity Measures for Author Cocitation Analysis
Full text linkWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Boosting or Attenuating? The Llinguistic Features of Sentiment Strength in User Generated Content
No full textAs markets have been labeled as conversations and consumer-to-consumer communications
have been recognized as a dominant force in driving consumer patronage, companies are facing
the challenge of having to resort to a new generation of performance metrics that provides guidance in a social commerce environment. With respect to this, sentiment analysis of text-based. User Generated Content (UCG) has become an increasingly popular way of staying in touch with customers. The viability of sentiment analysis as a performance metric, however, has been seriously questioned due to its limited predictive ability in assessing diverging degrees of positive and negative sentiments embedded in large and diverse volumes of online textual conversations. In this study, we advance automated text-mining modeling, based on linguistic theory, to deal with aforementioned issues. On the basis of emergent theorizing on speech acts, we zoom in on how linguistic style elements -modal and relational meaning- can boost or attenuate sentiment expression in online customer reviews. The modality of sentiment is accounted for by considering arousal intensity of affect-laden words. Moreover, commonalities of linguistic style elements on the basis of function words, such as pronouns, tenses and word interlinks (patterns) reflect conversants’ alliance or relational closeness to a consensual style of interaction. This is referred to as linguistic style matching. We test our theory-based predictions by examining more than
100.000 reviews across a range of 8 different product/service categories. The empirical results
show that adding aforementioned linguistic elements increases the predictive ability of a sentiment classification model of customer online reviews, allowing firms to develop better quantitative metrics from online textual information. Finally, we corroborate our approach in sampled Facebook and Twitter conversations. Theoretical and managerial implications are discusse
Dispelling the Myths Behind First-author Citation Counts
Full text linkWe conducted a full-scale evaluative citation analysis study of scholars in the XML research field to explore just how different from each other author rankings resulting from different citation counting methods actually are, and to demonstrate the capability of emerging data and tools on the Web in supporting more realistic citation counting methods. Our results contest some common arguments for the continued
use of first-author citation counts in the evaluation of scholars, such as high correlations between author rankings by first-author citation counts and other citation
counting methods, and high costs of using more realistic citation counting methods that are not well-supported by the ISI databases. It is argued that increasingly available digital full text research papers make it possible for citation analysis studies to go beyond what the ISI databases have directly supported and to employ more
sophisticated methods
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