Socio-semantic networks as mutualistic networks

St-Onge, Jonathan; Renaud-Desjardins, Louis; Mongeau, Pierre; Saint‐Charles, Johanne

doi:10.1038/s41598-022-05743-5

Cited by 4 publications

(2 citation statements)

References 57 publications

(66 reference statements)

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“…A social network facilitates the exchange of information and knowledge (Wu et al 2017 ; Camacho et al 2020 ; Aggrawal and Anand 2022 ) by connecting various entities through social relationships (Wasserman and Faust 1994 ; St-Onge et al 2022 ). To understand the impact of this kind of network on group behavior and individual influence, SNA can be used to describe its structure (Wasserman and Faust 1994 ).…”

Section: Social Network Analysis and Decision-making Support For Airl...mentioning

confidence: 99%

Enhancing decision-making support by mining social media data with social network analysis

Freire

Antunes

Costa

2023

Soc. Netw. Anal. Min.

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This paper explores the use of social network analysis (SNA) on airlines’ online social networks (OSNs) to extract valuable information for decision support, by analyzing interactions and discursive exchanges between users. The research is focused on fostering customer service of an airline company during a strike period, namely by detecting influential customers (whether satisfied or dissatisfied), address pending requests, and enhancing customer satisfaction, thus promoting issue-solving, and increasing responsiveness. The methodology involves analyzing data from the Facebook account of an airline company, using SNA to structure the data, and calculating metrics to detect possible situations to be addressed by customer service. The research concludes that it is possible to extract valuable information for decision support by analyzing the metrics that were built over the interactions and discursive exchanges between OSN users. SNA metrics enable to measure airline’s call-center performance in terms of speed of answer and customer satisfaction, to identify active users requiring additional support, as well as highly influential customers who may impact on the overall customer satisfaction, thus helping to resolve issues more efficiently. This study provides both theoretical and practical implications: it contributes to the existing literature by integrating social interaction and SNA for decision support in airline’s service context; and it provides practical insights into how companies can use SNA metrics to improve customer service. The research also highlights and corroborates the importance of monitoring social media interactions for decision-making and improving customer service.

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Section: Social Network Analysis and Decision-making Support For Airl...mentioning

confidence: 99%

Enhancing decision-making support by mining social media data with social network analysis

Freire

Antunes

Costa

2023

Soc. Netw. Anal. Min.

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“…Phenology, which is mostly related to climate, plant, and animal's life, is the study of cyclical and seasonal natural occurrences (Taylor and White, 2020). Climate change in uences the phenology, local abundance and population dissemination of plants and pollinators (Hegland et al, 2009a) Mutualistic interaction between species exists in every ecosystem, and plant-pollinator interactions are excellent examples of mutualism (Kawata and Takimoto, 2023;St-Onge et al, 2022). Approximately 85% of angiosperm plant species and 33% of the world's cultivated crops are pollinated by animals; insects play the largest part in this ecological service (Burkle, Marlin andKnight, 2013b;Buxton et al, 2022;Potts et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

Global trends, knowledge mapping and visualization of current research on climate change and their impact on plant-pollinators interaction

Singh,

Gargi,

Semwal

2023

Preprint

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The mutualistic interactions between plants and pollinators is one of the most prestigious field of research in ecology, which give information on the biotic network architecture, coexistence, diversification, and ecosystem function. In this manuscript, our research intends to identify the published literature for research production, collaborations, hotspots, and trends in research addressing the influence of climate change on the relationship between plants and pollinators. The research and review papers on the interactions between plants and pollinators, and climate change published in the Scopus database were retrieved. The contribution of nations, journals, institutions, current trends, and keyword analysis were shown using VOSviewer and RStudio bibliometrix to produce a network map of author collaboration across nations. The Scopus database (2007 to 2023) yielded a total of 256 entries, of which 229 publications were examined after being excluded based on various criteria. As per our data analysis, “The Rocky Mountain Biological Laboratory” and “Journal of Ecology” were the most effective organization, and journal, respectively. The author with the most publications was “Laura A. Burkle” of “Montana State University”. The “United States” is rated #1 among all nations in terms of the global production of literature on the effects of climate change on interactions between plant and pollinators. We determined four primary research subjects and new research areas for further study through the analysis of keywords. This study highlights current research on the effects of climate change on plant-pollinator relationships and is an early attempt to understand how these connections form and alter. The majority of recent research has been on the effects of drought on plants in these systems, which is a developing field of study that requires attention from academics for future research.

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Metrics for Temporal Text Networks

Vega,

Magnani

2023

Computational Social Sciences

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Human communication, either online or offline, is characterized by when information is shared from one actor to the other and by what specific information is exchanged. Using text as a way to represent the exchanged information, we can represent human communication systems with a temporal text network model where actors and messages coexist in a dynamic multilayer network. In this model, actors and messages are represented in separate layers, connected by inter-layer temporal edges representing the communication acts -who and when communicate what information. In this chapter we revisit some measures specifically developed for temporal networks, and extend them to the case of temporal text networks. In particular, we focus on defining measures relevant for the analysis of information propagation, including the concepts of walk, path, temporal precedence and path distance measures. We conclude by discussing how to use the proposed measures in practice by conducting a comparative analysis in a sample communication network based on Twitter mentions.

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Socio-semantic networks as mutualistic networks

Cited by 4 publications

References 57 publications

Enhancing decision-making support by mining social media data with social network analysis

Enhancing decision-making support by mining social media data with social network analysis

Global trends, knowledge mapping and visualization of current research on climate change and their impact on plant-pollinators interaction

Metrics for Temporal Text Networks

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