1,721,012 research outputs found

    A Comparison of Different Topic Modeling Methods through a Real Case Study of Italian Customer Care

    Full text link
    The paper deals with the analysis of conversation transcriptions between customers and agents in a call center of a customer care service. The objective is to support the analysis of text transcription of human-to-human conversations, to obtain reports on customer problems and complaints, and on the way an agent has solved them. The aim is to provide customer care service with a high level of efficiency and user satisfaction. To this aim, topic modeling is considered since it facilitates insightful analysis from large documents and datasets, such as a summarization of the main topics and topic characteristics. This paper presents a performance comparison of four topic modeling algorithms: (i) Latent Dirichlet Allocation (LDA); (ii) Non-negative Matrix Factorization (NMF); (iii) Neural-ProdLDA (Neural LDA) and Contextualized Topic Models (CTM). The comparison study is based on a database containing real conversation transcriptions in Italian Natural Language. Experimental results and different topic evaluation metrics are analyzed in this paper to determine the most suitable model for the case study. The gained knowledge can be exploited by practitioners to identify the optimal strategy and to perform and evaluate topic modeling on Italian natural language transcriptions of human-to-human conversations. This work can be an asset for grounding applications of topic modeling and can be inspiring for similar case studies in the domain of customer care quality

    An Assessment of Digitalization Techniques in Contact Centers and Their Impact on Agent Performance and Well-Being

    Full text link
    The role of contact centers in improving the operational efficiency of numerous organizations is of utmost importance. Presently, digitalization technology has enabled contact centers to deliver exceptional customer service and support, while minimizing the adverse impact on agent well-being. Artificial intelligence techniques such as topic modeling and sentiment analysis can aid agents in addressing specific queries, providing real-time support and feedback, and helping them build stronger relationships with customers. This study aims to investigate the advantages of integrating these techniques in the analysis of customer–agent conversations within contact centers. This study examines whether there is a discernible advantage in analyzing customer–agent conversations in real-time and whether it is worth using this type of digitization to enhance agent performance and well-being. Furthermore, this study explores the impact of these technologies on European privacy, business, real-time agent support, the value of conversation data, brand reputation, and customer satisfaction. The results of this study demonstrate the significance of incorporating topic modeling and sentiment analysis into the analysis of customer–agent conversations at contact centers

    Topic Modeling for Automatic Analysis of Natural Language: A Case Study in an Italian Customer Support Center

    Full text link
    This paper focuses on the automatic analysis of conversation transcriptions in the call center of a customer care service. The goal is to recognize topics related to problems and complaints discussed in several dialogues between customers and agents. Our study aims to implement a framework able to automatically cluster conversation transcriptions into cohesive and well-separated groups based on the content of the data. The framework can alleviate the analyst selecting proper values for the analysis and the clustering processes. To pursue this goal, we consider a probabilistic model based on the latent Dirichlet allocation, which associates transcriptions with a mixture of topics in different proportions. A case study consisting of transcriptions in the Italian natural language, and collected in a customer support center of an energy supplier, is considered in the paper. Performance comparison of different inference techniques is discussed using the case study. The experimental results demonstrate the approach’s efficacy in clustering Italian conversation transcriptions. It also results in a practical tool to simplify the analytic process and off-load the parameter tuning from the end-user. According to recent works in the literature, this paper may be valuable for introducing latent Dirichlet allocation approaches in topic modeling for the Italian natural language

    Going Beyond Counting First Authors in Author Co-citation Analysis

    Full text link
    The 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

    Observation of phonon-polaritons in thin flakes of hexagonal boron nitride on gold

    No full text
    Hexagonal Boron Nitride (hBN) is a layered van der Waals material able to sustain hyperbolic phonon-polaritons within its mid-infrared reststrahlen bands. We study the effect of a metallic substrate adjacent to hBN flakes on the polariton dispersion and on the standing wave patterns in nanostructures by means of mid-infrared nanospectroscopy and nanoimaging. We exploit the gold-coated tip apex for atomic force microscopy to launch polaritons in thin hBN flakes. The photo-thermal induced mechanical resonance is used to detect the amplitude profile of polariton standing waves with a lateral resolution of 30 nm. We observe the polariton excitation spectra on hBN flakes as thin as 4 nm, thanks to the infrared field enhancement in the nanogap between the gold-coated tip apex and an ultraflat gold substrate. The data indicate no major effect of remote screening of the free electrons in gold on the phonon-polariton excitation that appears robust also against geometrical imperfections

    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 link
    We 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

    Dispelling the Myths Behind First-author Citation Counts

    Full text link
    We 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
    corecore