scholarly journals Sosiaalisen median hyödyntäminen nuorten palvelujen yhteiskehittämisessä

2021 ◽  
Vol 40 (1) ◽  
pp. 5-22
Author(s):  
Harri Jalonen ◽  
Jussi Kokkola ◽  
Valtteri Kaartemo ◽  
Miika Vähämaa
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Discourse Analysis ◽  
Knowledge Base ◽  
Empirical Data ◽  
Discussion Forum ◽  
Discussion Board ◽  
Dynamic Relationship ◽  
The Everyday ◽  
Using Data

Co-creation assumes an interactive and dynamic relationship where value is created at the nexus of interaction. Co-creating value is challenging with marginalized youths. In this article, social media is seen as an underutilized resource for developing services. This article approaches social media as a context from which it is possible to derive information that would otherwise be unattainable. Using data from a Finnish discussion board, this article answers the following question: How can the experiences of socially withdrawn youth shared on social media be used to enrich the knowledge base on service co-creation processes? The empirical data consist of messages on the Hikikomero discussion forum, which were analysed using a combination of unsupervised machine learning and discourse analysis. The results show that social media provides a window into the everyday lives of socially withdrawn youths, offering information that could be used to develop public services

Deep Learning and Machine Learning Techniques for Analyzing Travelers' Online Reviews

2022 ◽  
pp. 20-39
Author(s):  
Elliot Mbunge ◽  
Benhildah Muchemwa
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Deep Learning ◽  
Hospitality Industry ◽  
Learning Models ◽  
Online Data ◽  
Social Media Platforms ◽  
Using Data ◽  
Tourism And Hospitality Industry ◽  
Tourism And Hospitality

Social media platforms play a tremendous role in the tourism and hospitality industry. Social media platforms are increasingly becoming a source of information. The complexity and increasing size of tourists' online data make it difficult to extract meaningful insights using traditional models. Therefore, this scoping and comprehensive review aimed to analyze machine learning and deep learning models applied to model tourism data. The study revealed that deep learning and machine learning models are used for forecasting and predicting tourism demand using data from search query data, Google trends, and social media platforms. Also, the study revealed that data-driven models can assist managers and policymakers in mapping and segmenting tourism hotspots and attractions and predicting revenue that is likely to be generated, exploring targeting marketing, segmenting tourists based on their spending patterns, lifestyle, and age group. However, hybrid deep learning models such as inceptionV3, MobilenetsV3, and YOLOv4 are not yet explored in the tourism and hospitality industry.

scholarly journals Reaching hard-to-reach people through digital means – Citizens as initiators of co-creation in public services

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Harri Jalonen ◽  
Jussi Kokkola ◽  
Harri Laihonen ◽  
Hanna Kirjavainen ◽  
Valtteri Kaartemo ◽  
...  
Keyword(s):  
Social Media ◽  
Knowledge Base ◽  
Public Services ◽  
Evidence Base ◽  
Content Type ◽  
Initiation Phase ◽  
Dynamic Relationship ◽  
Managerial Implications ◽  
Digital Stories

PurposeThis paper considers the potential of social media for developing public services. The paper approaches social media as a context that can provide information that might otherwise be unattainable. The focus of analysis is on a special hard-to-reach group of marginalized youths who appear to have isolated themselves from society.Design/methodology/approachThe authors answer the question: How can the experiences of socially withdrawn youth as shared on social media be used to enrich the knowledge base relating to the initiation phase of co-creation of public services? The data retrieved from the Finnish discussion forum are analyzed using the combination of unsupervised machine learning and discourse analysis.FindingsThe paper contributes by outlining a method that can be applied to identify expertise-by-experience from digital stories shared by marginalized youths. To overcome the challenges of making socially withdrawn youths real contributors to the co-creation of public services, this paper suggests several theoretical and managerial implications.Originality/valueCo-creation assumes an interactive and dynamic relationship where value is created at the nexus of interaction. However, the evidence base for successful co-creation, particularly with digital technology, is limited. This paper fills the gap by providing findings from a case study that investigated how social media discussions can be a stimulus to enrich the knowledge base of the co-creation of public services.

scholarly journals ETHNICITY IN THE ELECTORAL DIMENSION OF THE IDENTITY POLICY OF THE RUSSIAN REPUBLICS: BETWEEN UNIVERSAL AND PARTICULAR

2020 ◽  
Vol 14 (4) ◽  
pp. 39-49
Author(s):  
Regina Petrova ◽  
◽  
Evgenia Filippova ◽  
Keyword(s):  
Social Media ◽  
Discourse Analysis ◽  
Empirical Data ◽  
Research Method ◽  
Media Content ◽  
Election Campaign ◽  
Dominant Form ◽  
Symbolic Model ◽  
Identity Policy

The article presents the results of the research of the pre-election discourse of candidates for governors of national republics during the last elections from the perspective of the concept of the institutionalization of ethnicity in the identity policy. The aim of the article is to determine the form of institutionalization of ethnicity in the electoral dimension of identity policies implemented in the context of the election campaign of governors and considering the ethnic structure of the republics' population. The research method is a comparative discourse analysis. The empirical data used are media content, election programs, and campaign materials of candidates from their social media accounts. The dominant form of institutionalization of ethnicity is a «symbolic model» in which ethnicity is defined as a symbol of the republic’s uniqueness. Dependence between the choice of such form of institutionalization in pre-election discourse and specifics of the national composition of the republic’s population does not occur in all cases. One of the most common forms of institutionalization of ethnicity is «predominantly without ethnicity». However, the interim governors rarely chose this model.

Utilizing Blockchain Technology in Social Media Bot Identification

2020 ◽  
Author(s):  
Shreya Reddy ◽  
Lisa Ewen ◽  
Pankti Patel ◽  
Prerak Patel ◽  
Ankit Kundal ◽  
...  
Keyword(s):  
Machine Learning ◽  
Social Media ◽  
Gold Standard ◽  
The Internet ◽  
Learning Models ◽  
Current Time ◽  
Machine Learning Methods ◽  
Blockchain Technology ◽  
Modern Age ◽  
Machine Learning Models

<p>As bots become more prevalent and smarter in the modern age of the internet, it becomes ever more important that they be identified and removed. Recent research has dictated that machine learning methods are accurate and the gold standard of bot identification on social media. Unfortunately, machine learning models do not come without their negative aspects such as lengthy training times, difficult feature selection, and overwhelming pre-processing tasks. To overcome these difficulties, we are proposing a blockchain framework for bot identification. At the current time, it is unknown how this method will perform, but it serves to prove the existence of an overwhelming gap of research under this area.<i></i></p>

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