Handling uncertainty in social media textual information for improving venue recommendation formulation quality in social networks

Margaris, Dionisis; Vassilakis, Costas; Spiliotopoulos, Dimitris

doi:10.1007/s13278-019-0610-x

Cited by 23 publications

(7 citation statements)

References 39 publications

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“…Marketing & sales approaches were more focused on customers, i.e., exploiting user information to improve communication and advertising campaigns. For example, by exploiting user generated content that includes geographical information to improve traveling marketing decisions [15] and recommend POI [79].…”

Section: B Business Value Chain Findingsmentioning

confidence: 99%

Location Data Analytics in the Business Value Chain: A Systematic Literature Review

2020

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Section: B Business Value Chain Findingsmentioning

confidence: 99%

Location Data Analytics in the Business Value Chain: A Systematic Literature Review

2020

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“…In addition, the number of active SMRS researchers is more than 50 links in most of the clusters, which shows its research strength. Co-author analysis is mainly for the measurement of author collaboration [98]- [100].…”

Section: Discussionmentioning

confidence: 99%

Social Media Recommender Systems (SMRS): A Bibliometric Analysis Study 2000–2021

et al. 2022

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The increasing popularity of social media resources such as blogs, bookmarks, chatrooms, forums and video portals in recent years has attracted diverse users. Following the rise of the Internet, online content has become overloaded, prompting the introduction of recommender systems on social media. As a result, research on the dynamic growth of recommender systems in social media has gained significant traction since the year 2000. Social media recommender systems (SMRS) utilize multiple recommendation fields such as item, user, location, tag, event, tour and game in searching for preferred recommended information. Thus, young research fellows, academic scholars and practitioners must understand the need for SMRS to be complemented with recommendation fields. This requirement underlines the significance of a bibliometric analysis that focuses on social media based on existing publications. Hence, using the Web of Science (WoS) database, this study aimed to gather statistical information on SMRS to help researchers acquire an extensive understanding of such systems. The analysis was conducted by identifying SMRS-related publications and scientometric indicators to assess the growth rate, including the relative growth rate (RGR), doubling time (DT) and the field-normalized citation score (NCSf)-for citation analysis. Overall, this bibliometric study provides relevant measures for comparing and improving the citation rate of publications for new researchers.

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“…For future work, we are planning to include an analysis of textual information from existing social network users for the automatic adaptation of existing personas with regard to their content description for a fully-fledged persona construction [48,49]. Additionally, multiple sources, such as Facebook, could be utilized for automatic enrichment, since users reported that they found interesting information and expected it to be a valid resource for cultural event-based user content.…”

Section: Discussionmentioning

confidence: 99%

Data-Assisted Persona Construction Using Social Media Data

Spiliotopoulos

Margaris

Vassilakis

2020

BDCC

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User experience design and subsequent usability evaluation can benefit from knowledge about user interaction, types, deployment settings and situations. Most of the time, the user type and generic requirements are given or can be obtained and used to model interaction during the design phase. The deployment settings and situations can be collected through the needfinding phase, either via user feedback or via the automatic analysis of existing data. Personas may be defined using the aforementioned information through user research analysis or data analysis. This work utilizes an approach to activate an accurate persona definition early in the design cycle, using topic detection to semantically enrich the data that are used to derive the persona details. This work uses Twitter data from a music event to extract information that can be used to assist persona creation. A user study in persona construction compares the topic modelling metadata to a traditional user collected data analysis for persona construction. The results show that the topic information-driven constructed personas are perceived as having better clarity, completeness and credibility. Additionally, the human users feel more attracted and similar to such personas. This work may be used to model personas and recommend suitable ones to designers of other products, such as advertisers, game designers and moviegoers.

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Handling uncertainty in social media textual information for improving venue recommendation formulation quality in social networks

Cited by 23 publications

References 39 publications

Location Data Analytics in the Business Value Chain: A Systematic Literature Review

Location Data Analytics in the Business Value Chain: A Systematic Literature Review

Social Media Recommender Systems (SMRS): A Bibliometric Analysis Study 2000–2021

Data-Assisted Persona Construction Using Social Media Data

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