When Digital Trace Data Meet Traditional Communication Theory: Theoretical/Methodological Directions

2018 ◽  
Vol 38 (1) ◽  
pp. 91-107 ◽  
Author(s):  
Sujin Choi
Keyword(s):  
Language Processing ◽  
Communication Theory ◽  
Longitudinal Change ◽  
Communication Research ◽  
Human Communication ◽  
Power Law Distribution ◽  
Trace Data ◽  
Automated Content Analysis ◽  
Processing Techniques ◽  
Social Science Approach

This study suggests one direction of theoretical and methodological coupling of communication research with the digital trace data, utilizing its differences from the traditional social science approach (e.g., sampling vs. population, normal distribution vs. power–law distribution, generalization vs. simulation, deductive vs. inductive, and perceived vs. actual). We propose specific examples of (i) combining communication research with trace data methodologically and theoretically; (ii) collaborating with linguistic psychology complemented with the automated content analysis and natural language processing techniques; and (iii) creating new theoretical inquiries by configuring the granular level of interactivity and underlying dynamics, observing the longitudinal change of interactions, and discovering the neglected presence of outliers and the invisibles. We expect the direction suggested by this study contributes to deepening our understanding of human communication behavior.

scholarly journals Gender (in)equality in Chilean press: journalists and sources

2021 ◽  
Vol 20 (2) ◽  
pp. 259-275
Author(s):  
Marta Mensa Torras ◽  
Matthieu Vernier ◽  
Luís Cárcamo-Ulloa ◽  
Fabían Ruíz ◽  
Boris Sotomayor-Gómez
Keyword(s):  
Gender Bias ◽  
Language Processing ◽  
Computational Social Science ◽  
Significant Finding ◽  
Social Phenomena ◽  
Female Journalists ◽  
The Media ◽  
Processing Techniques ◽  
Media Power ◽  
Social Science Approach

Who writes the news in the Chilean press according to gender? Who are the sources, male or female, in the Chilean press? Is there a relationship between the gender of journalists and the gender of the sources in the Chilean press? This article studies the gender of the Chilean newsroom and their sources in 12,113 news through a quantitative method with a computational social science approach. This method combines web scraping and natural language processing techniques to gather and preprocess data, facilitating the exploration of complex social phenomena. Results show important biases in journalists and source gender. From a sample of 158 journalists, 99 were men (63%) and 59 women (37%). Also, from 12,113 news, 7,565 (62%) were written by male and 4,548 (38%) by female journalists. Of the 12,334 sources mentioned in the news, 9,771 were men (79%) and 2,563 were women (21%). A significant finding is that equality in the newsroom is related to how female and male journalists choose their sources. In other words, when a media has a newsroom with gender equality, the sources of the journalists are more equitable too. These results have important insights to discuss within the journalism schools, to make students aware of the gender bias in the profession. Furthermore, if the presence of female – journalists or sources- increased in the media, it would allow them to grow their media power and status.

Artificial intelligence and communication: A Human–Machine Communication research agenda

2019 ◽  
Vol 22 (1) ◽  
pp. 70-86 ◽  
Author(s):  
Andrea L Guzman ◽  
Seth C Lewis
Keyword(s):  
Artificial Intelligence ◽  
Research Agenda ◽  
Communication Theory ◽  
Virtual Agents ◽  
Communication Research ◽  
Human Communication ◽  
Relational Dynamics ◽  
Starting Point ◽  
Key Aspects ◽  
Machine Communication

Artificial intelligence (AI) and people’s interactions with it—through virtual agents, socialbots, and language-generation software—do not fit neatly into paradigms of communication theory that have long focused on human–human communication. To address this disconnect between communication theory and emerging technology, this article provides a starting point for articulating the differences between communicative AI and previous technologies and introduces a theoretical basis for navigating these conditions in the form of scholarship within human–machine communication (HMC). Drawing on an HMC framework, we outline a research agenda built around three key aspects of communicative AI technologies: (1) the functional dimensions through which people make sense of these devices and applications as communicators, (2) the relational dynamics through which people associate with these technologies and, in turn, relate to themselves and others, and (3) the metaphysical implications called up by blurring ontological boundaries surrounding what constitutes human, machine, and communication.

scholarly journals Twitter Sentiment Analysis towards COVID-19 Vaccines in the Philippines Using Naïve Bayes

Information ◽  
2021 ◽  
Vol 12 (5) ◽  
pp. 204
Author(s):  
Charlyn Villavicencio ◽  
Julio Jerison Macrohon ◽  
X. Alphonse Inbaraj ◽  
Jyh-Horng Jeng ◽  
Jer-Guang Hsieh
Keyword(s):  
Sentiment Analysis ◽  
Language Processing ◽  
Data Science ◽  
Naive Bayes ◽  
The Philippines ◽  
Naïve Bayes ◽  
Social Networking Site ◽  
Bayes Model ◽  
The Government ◽  
Processing Techniques

A year into the COVID-19 pandemic and one of the longest recorded lockdowns in the world, the Philippines received its first delivery of COVID-19 vaccines on 1 March 2021 through WHO’s COVAX initiative. A month into inoculation of all frontline health professionals and other priority groups, the authors of this study gathered data on the sentiment of Filipinos regarding the Philippine government’s efforts using the social networking site Twitter. Natural language processing techniques were applied to understand the general sentiment, which can help the government in analyzing their response. The sentiments were annotated and trained using the Naïve Bayes model to classify English and Filipino language tweets into positive, neutral, and negative polarities through the RapidMiner data science software. The results yielded an 81.77% accuracy, which outweighs the accuracy of recent sentiment analysis studies using Twitter data from the Philippines.

scholarly journals Shall I Work with Them? A Knowledge Graph-Based Approach for Predicting Future Research Collaborations

Entropy ◽  
2021 ◽  
Vol 23 (6) ◽  
pp. 664
Author(s):  
Nikos Kanakaris ◽  
Nikolaos Giarelis ◽  
Ilias Siachos ◽  
Nikos Karacapilidis
Keyword(s):  
Language Processing ◽  
Scientific Knowledge ◽  
Link Prediction ◽  
Performance Metrics ◽  
Future Research ◽  
Knowledge Graph ◽  
Prediction Problem ◽  
Textual Information ◽  
Research Collaborations ◽  
Processing Techniques

We consider the prediction of future research collaborations as a link prediction problem applied on a scientific knowledge graph. To the best of our knowledge, this is the first work on the prediction of future research collaborations that combines structural and textual information of a scientific knowledge graph through a purposeful integration of graph algorithms and natural language processing techniques. Our work: (i) investigates whether the integration of unstructured textual data into a single knowledge graph affects the performance of a link prediction model, (ii) studies the effect of previously proposed graph kernels based approaches on the performance of an ML model, as far as the link prediction problem is concerned, and (iii) proposes a three-phase pipeline that enables the exploitation of structural and textual information, as well as of pre-trained word embeddings. We benchmark the proposed approach against classical link prediction algorithms using accuracy, recall, and precision as our performance metrics. Finally, we empirically test our approach through various feature combinations with respect to the link prediction problem. Our experimentations with the new COVID-19 Open Research Dataset demonstrate a significant improvement of the abovementioned performance metrics in the prediction of future research collaborations.

scholarly journals A Natural Language Processing Approach to Measuring Treatment Adherence and Consistency Using Semantic Similarity

AERA Open ◽  
2021 ◽  
Vol 7 ◽  
pp. 233285842110286
Author(s):  
Kylie L. Anglin ◽  
Vivian C. Wong ◽  
Arielle Boguslav
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Semantic Similarity ◽  
Language Processing ◽  
Intervention Implementation ◽  
Proof Of Concept ◽  
Coaching Intervention ◽  
Processing Techniques ◽  
Teacher Coaching ◽  
The Impact

Though there is widespread recognition of the importance of implementation research, evaluators often face intense logistical, budgetary, and methodological challenges in their efforts to assess intervention implementation in the field. This article proposes a set of natural language processing techniques called semantic similarity as an innovative and scalable method of measuring implementation constructs. Semantic similarity methods are an automated approach to quantifying the similarity between texts. By applying semantic similarity to transcripts of intervention sessions, researchers can use the method to determine whether an intervention was delivered with adherence to a structured protocol, and the extent to which an intervention was replicated with consistency across sessions, sites, and studies. This article provides an overview of semantic similarity methods, describes their application within the context of educational evaluations, and provides a proof of concept using an experimental study of the impact of a standardized teacher coaching intervention.

Exploring Library Core Competencies: A Text Mining Study of American Library Association’s Job Advertisements From 2006 Through 2017

2021 ◽  
pp. 089443932110272
Author(s):  
Qinghong Yang ◽  
Zehong Shi ◽  
Yan Quan Liu
Keyword(s):  
Language Processing ◽  
Work Experience ◽  
Core Competencies ◽  
Core Competency ◽  
Analytical Investigation ◽  
Market Demand ◽  
American Library ◽  
Job Titles ◽  
Job Advertisements ◽  
Processing Techniques

Are core competency requirements for relevant positions in the library shifting? Applying natural language processing techniques to understand the current market demand for core competencies, this study explores job advertisements issued by the American Library Association (ALA) from 2006 to 2017. Research reveals that the job demand continues to rise at a rate of 13% (2006–2017) and that the requirements for work experience are substantially extended, diversity of job titles becomes prevalent, and rich service experience and continuous lifelong learning skills are becoming more and more predominant for librarians. This analytical investigation informs the emerging demands in the American job market debriefing the prioritization and reprioritization of the current core competency requirements for ALA librarians.

Compansion: From research prototype to practical integration

1998 ◽  
Vol 4 (1) ◽  
pp. 73-95 ◽  
Author(s):  
KATHLEEN F. MCCOY ◽  
CHRISTOPHER A. PENNINGTON ◽  
ARLENE LUBEROFF BADMAN
Keyword(s):  
Language Processing ◽  
Augmentative And Alternative Communication ◽  
Communication Aids ◽  
Alternative Communication ◽  
Communicative Ability ◽  
Linguistic Ability ◽  
Research Prototype ◽  
Intelligent Communication ◽  
Processing Techniques ◽  
Parser Generator

Augmentative and Alternative Communication (AAC) is the field of study concerned with providing devices and techniques to augment the communicative ability of a person whose disability makes it difficult to speak or otherwise communicate in an understandable fashion. For several years, we have been applying natural language processing techniques to the field of AAC to develop intelligent communication aids that attempt to provide linguistically correct output while increasing communication rate. Previous effort has resulted in a research prototype called Compansion that expands telegraphic input. In this paper we describe that research prototype and introduce the Intelligent Parser Generator (IPG). IPG is intended to be a practical embodiment of the research prototype aimed at a group of users who have cognitive impairments that affect their linguistic ability. We describe both the theoretical underpinnings of Compansion and the practical considerations in developing a usable system for this population of users.

Communication Theory and Training Approaches for Multiculturally Diverse Organizations: Have Academics and Practitioners Missed the Connection?

2001 ◽  
Vol 30 (4) ◽  
pp. 445-455 ◽  
Author(s):  
Marguerite Arai ◽  
Maryanne Wanca-Thibault ◽  
Pamela Shockley-Zalabak
Keyword(s):  
Communication Theory ◽  
Diversity Training ◽  
Multicultural Training ◽  
Theory And Practice ◽  
Important Research ◽  
Human Communication ◽  
The Past ◽  
The Common ◽  
Multiculturally Diverse ◽  
And Training

While a number of articles have looked at the importance of multicultural training in the workplace over the past 30 years, there is little concrete agreement that documents the common fundamental elements of a “successful” diversity initiative. A review of the training literature suggests the importance of human communication theory and practice without including important research, methodologies, and practice from the communication discipline. This article examines formal diversity approaches, provides examples from the literature of several successful diversity initiatives in larger organizations, identifies the limited use of communication-based approaches in diversity training, and discusses the importance of integrating communication theory and practice in future training efforts.

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