Tag Ontology Research Articles

(096) #SexMed: The Sexual Medicine Tag Ontology Project

Abstract Introduction Female sexual dysfunction includes many different conditions that involve desire, arousal, orgasm, and pain. More than 40% of American women report sexual problems and nearly 12% meet the criteria for a diagnosed sexual dysfunction. Given the sensitivity of the topic, many women turn to the Internet to find information. In specific, social media allows users to interact with others by creating, viewing and commenting on content. “Hashtags” are a type of metadata tag that are preceded by the symbol “#”. By adding this symbol, social media platforms are able to compile relevant information in a single place, streamlining pertinent information and allowing for users to find others with similar interests and create new communities based on a common interest. Objective The aim of this study is to develop a tag ontology and to identify the top social media influencers for female sexual medicine. Methods Symplur is a Twitter analytic tool that identifies tweets and hashtags related to a specific topic. This software was used to create a “tag ontology”, a standardized list of hashtags, using the search terms “sexual medicine”, “women’s sexual health” and “female sexual dysfunction” between November 1, 2020 and November 1, 2022. The hashtag ontology list created by Symplur was then reviewed by social media influencers for inclusivity and external validation. A proprietary Symplur algorithm was used to identify Top Influencers. Results We identified 3800 tweets during the study time period. In total, the ontology included 22 terms (Table 1). Medical and vernacular terms were included in the “tag ontology” so the list included terms accessible to both women and healthcare providers. Of the top 20 influencers, 10 were physicians, 7 were major medical societies, 2 were academic journals and 1 was industry related. A visual of the top 15 influencers appears in Figure 1. Conclusions Creation of a standardized hashtag ontology consolidates communication between healthcare providers and patients about specific health information. Our study has created a “tag ontology” for female sexual medicine that can be utilized to streamline pertinent information between providers and women. Disclosure No

Who's Posting What? A Qualitative, Cross-Sectional Study Comparing Twitter and Instagram Patterns Between Health Care Professionals and Patients.

There is a paucity of evidence-based, physician-authored content available on social media. Data are lacking on physicians use of social media, including intended audience and content. The aim of this study was to explore the patterns of Twitter and Instagram use for popular urogynecology hashtags between physicians, patients, and allied health professionals (AHPs). Twelve hashtags derived from the Urogynecology Tag Ontology project were used as search terms to select Twitter and Instagram posts. Up to 5 top posts per hashtag per author type (physician, patient, or AHP) were included. Posts were analyzed using Dedoose qualitative analytic software by author, hashtag, intended audience, and themes. On Twitter, 109 posts met inclusion criteria: 41% written by physicians, 40% patients, and 18.3% AHPs. For Instagram, 72 posts were included: 50% written by patients, 39% AHPs, and 11% physicians. Twitter physician posts were mainly intended for health professionals (64%) with only 18% for patients. Patients posted to the general public (57%) and patients (36%). Instagram physician posts were intended for health professionals (49%), whereas 62% of AHPs posted to patients. Most patient posts were directed to other patients (90%). Physicians posted about academic peer discussions, medical education, and advocacy. Patients posted about personal experiences, treatments, or dissatisfaction. Physicians are more likely to post on Twitter than Instagram, with content focused primarily on their peer group, and physicians/patients are unlikely to engage with each other. There is an opportunity to improve social media interactions between physicians and the public while increasing high-quality patient education.

#MIGS: Minimally Invasive Gynecologic Surgery Tag Ontology Project

The creation of an ontology may enable providers to more definitively engage the public in evidence-based and meaningful discussions about women's health. The goal of this study is to review and analyze the current social media status of minimally invasive gynecologic surgery (MIGS) on Twitter and create a tag ontology. Tag ontologies are lists of hashtags used to standardize searches within a social media platform. We examined trending terms and influencers on Twitter on the basis of the keyword "MIGS." We then compiled a list of top hashtags on the basis of the number of tweets from January 2018 to August 2020. Terms were identified with manual Twitter queries and Symplur Signals and selected for inclusion in the ontology on the basis of frequency of use and clinical relevance. The ontology was then categorized by pelvic disease and intervention and reviewed/supplemented by key social media influencers for inclusivity. N/A PATIENTS: N/A INTERVENTIONS: N/A MEASUREMENTS AND MAIN RESULTS: We identified 4550 tweets and 1836 users while searching #MIGS in August 2020. Twenty-nine terms were included in our ontology, which were then subcategorized into 6 groups (uterine pathology, adnexal pathology, menstruation, pelvic pathology, pelvic pain, and other). Our study has created an ontology specific to the MIGS on the basis of Twitter usage over the last 2 years that may facilitate more effective social media communication.

#UTOPia: Urogynecology Tag Ontology Project.

The objective of this study was to review and analyze the current social media status of urogynecology/female pelvic medicine and reconstructive surgery on Twitter and create a tag ontology. A "tag ontology" is a standardized list of hashtags used to organize specific subject matter within a social media platform. We used an online social media analytics tool, Symplur to identify tweets and hashtags related to #urogynecology between January 2018 and July 2020. Hashtags identified using Symplur were verified manually via Twitter inquiries and reviewed by urogynecology social medial influencers for external validation. The hashtags were selected based on frequency of use, social media influencer opinion, and clinical relevance. We identified 6,847 tweets and 2,946 users. Our ontology includes 67 terms categorized into 5 groups (urinary, prolapse, anus/rectum, vulva, and other). Using "Symplur Rank," the 2 top influencers included @FPMRS and @FPMRSJournal. Adaptation of a standardized hashtag ontology facilitates communication between providers and patients about pertinent health care issues. Our study has created a urogynecology-specific ontology based on 2018-2020 Twitter usage.

“Six Things Are Said Concerning Demons” (Hagigah 16a). The System of Topic Tags Used in the Elyonim veTachtonim Inventory to Describe the Features of Supernatural Entities and Their Relationships with Humans

This paper has two main purposes: to outline the methodology underlying the tag ontology utilised in the Elyonim veTachtonim inventory and to demonstrate the system of topic tags used to designate recurring subjects recognised in the accounts involving supernatural entities.

Toward building recommender systems for the circular economy: Exploring the perils of the European Waste Catalogue

The growth in the number of industries aiming at more sustainable business processes is driving the use of the European Waste Catalogue (EWC). For example, the identification of industrial symbiosis opportunities, in which a user-generated item description has to be annotated with exactly one EWC tag from an a priori defined tag ontology. This study aims to help researchers understand the perils of the EWC when building a recommender system based on natural language processing techniques. We experiment with semantic enhancement (an EWC thesaurus) and the linguistic contexts of words (learned by Word2vec) for detecting term vector similarity in addition to direct term matching algorithms, which often fail to detect an identical term in the short text generated by users. Our in-depth analysis provides an insight into why the different recommenders were unable to generate a correct annotation and motivates a discussion on the current design of the EWC system.

Organizing Online Health Content: Developing Hashtag Collections for Healthier Internet-Based People and Communities.

Twitter use has increased among patients with cancer, advocates, and oncology professionals. Hashtags, a form of metadata, can be used to share content, organize health information, and create virtual communities of interest. Cancer-specific hashtags modeled on a breast cancer community, #bcsm, led to the development of a structured set of hashtags called the cancer tag ontology. In this article, we review how these hashtags have worked with the aim of describing our experience from 2011 to 2017. We discuss useful guidelines for the development and maintenance of health-oriented communities on Twitter, including possible challenges to community sustainability and opportunities for future improvement and research.

Quantification of Urology Related Twitter Traffic Activity through a Standardized List of Social Media Communication Descriptors

IntroductionThe social media microblogging service Twitter is gaining popularity in the field of urology as a fast and effective communication platform. We assessed volume, subject matter, influencers and content of urology related discussions on the Twitter platform using the recently proposed Urology Tag Ontology hashtag list. MethodsWe queried the Symplur Signals database for tweet activity during a 1-year period. We used the Urology Tag Ontology hashtag list, comprised of 45 disease related hashtags in 9 urological subspecialties, to assess activity (numbers of tweets, users and impressions), users (geolocation, influencers) and content (words, tweet enhancements) of urology related Twitter traffic. ResultsTwitter activity during the study period included 334,642 tweets by 104,166 users with 1,397,107,305 impressions. Tweet activity varied among urological subspecialties and was largely dominated by urological oncology topics driven by #ProstateCancer. Users came from 224 countries and from all continents around the globe. Health care organizations accounted for the largest proportion of influencers (44%), followed by other individuals (22%) and physicians (13%). The top words were “prevent” (used 20,955 times), “cancer” (19,610), “follow” (19,169), “men” (19,165) and “condom” (18,425). The median (range) number of shares was 2,200 (1,414-8,854) for the top 10 links, 2,123 (1,878-2,737) for the top 10 retweets and 207 (12-438) for the top 10 photos. ConclusionsTwitter activity in the field of urology can be assessed using a standardized list of social media communication descriptors. The value of the Twitter communication platform is underscored by the large number of tweets and impressions in the urology space.

Activity, content, contributors, and influencers of the twitter discussion on urologic oncology

ObjectivesTo analyse the activity, content, contributors, and influencers of the Twitter discussion on urologic oncology. Materials and methodsWe performed a comprehensive quantitative and qualitative Twitter analysis for the hashtags #prostatecancer, #bladdercancer, #kidneycancer, and #testicularcancer. Symplur was used to analyse activity over different time periods and the top influencers of the Twitter discussion. Tweet Archivist and Twitonomy analysis tools were used to assess characteristics of content and contributors. ResultsTwitter discussion on urologic oncology in 2014 contained 100,987 tweets created by 39,326 participants. Mean monthly tweet activity was 6,603±2,183 for #prostatecancer, 866±923 for #testicularcancer, 457±477 for #bladdercancer and 401±504 for #kidneycancer. Twitter activity increased by 41% in 2013 and by 122% in 2014. The content analysis detected awareness, cancer, and risk as frequently mentioned words in urologic oncology tweets. Prevalently used related hashtags were the general hashtag #cancer, awareness hashtags, and the respective cancer/urology tag ontology hashtags. Contributors originated from 41 countries on 6 continents and had a mean of 5,864±4,747 followers. They tweeted from platforms on exclusively mobile devices (39%) more frequently than from desktop devices (29%). Health care organizations accounted for 58% of the top influencers in all cancers. The largest proportion of physicians were among the #prostatecancer and #kidneycancer (each 9%) influencers and individual contributors were most frequent in the discussion on #kidneycancer (57%) and #testicularcancer (50%). ConclusionThere is a significant and growing activity in the Twitter discussion on urologic oncology, particularly on #prostatecancer. The Twitter discussion is global, social, and mobile, and merits attention of stakeholders in health care as a promising communication tool.

UniTag 온톨로지를 이용한 태그 기반 음악 추천 기법

본 논문에서는 소셜 음악 사이트에서 사용자들이 생성한 태그를 바탕으로 음악을 추천하는 기법을 제안한다. 협력적 태깅 시스템은 사용자가 직접 선정한 단어를 콘텐츠에 부여할 수 있도록 하므로, 사용자의 선호도를 구체적으로 파악할 수 있는 정보를 제공한다. 특히, 감정을 표현하는 감정 태그들은 음악 장르나 음악가와 같이 사실을 나타내는 사실 태그들과는 다르게 선호도를 훨씬 직접 표현하고 있다. 따라서 태그의 의미를 파악하여 감정 태그와 사실 태그로 분류하고, 감정 태그는 감정표현의 정도에 따라 가중치를 부여하기 위해서 UniTag라고 하는 태그 온톨로지를 개발하였다. UniTag 온톨로지를 이용하여 정제된 태그 집합은 사용자 프로파일 생성에 사용되며, 태그 기반 사용자 프로파일을 바탕으로 음악 추천 알고리즘을 수행하였다. 제안하는 추천 방법의 효율성을 평가하기 위해서, 전통적인 청취 횟수 기반 추천, 감정 태그 가중치를 고려하지 않은 추천, 그리고 감정 태그 가중치를 고려한 추천의 세 가지 추천 방법의 정확도와 재현율을 비교하였다. 실험 결과는, 감정 태그 가중치를 고려한 추천 방식이 정확도의 측면에서 다른 두 가지 방식보다 효율적이라는 것을 보여준다. In this paper, we propose a music recommendation method considering users' tags by collaborative tagging in a social music site. Since collaborative tagging allows a user to add keywords chosen by himself to web resources, it provides users' preference about the web resources concretely. In particular, emotional tags which represent human's emotion contain users' musical preference more directly than factual tags which represent facts such as musical genre and artists. Therefore, to classify the tags into the emotional tags and the factual tags and to assign weighted values to the emotional tags, a tag ontology called UniTag is developed. After preprocessing the tags, the weighted tags are used to create user profiles, and the music recommendation algorithm is executed based on the profiles. To evaluate the proposed method, a conventional playcount-based recommendation, an unweighted tag-based recommendation, and an weighted tag-based recommendation are executed. Our experimental results show that the weighted tag-based recommendation outperforms other two approaches in terms of precision.

Tag Ontology Automatic Building for Semantic Searching of Services: a Case Study on Mashup Services

The explosion of services like web services, APIs, Mashups, etc., makes how to find the right one you need a tough problem. Tags, as a kind of metadata have been widely used to annotate services. In this paper, we propose to use an ontology automatically built from tags to improve the performance of service searching. We use the famous Mashup directory, Programmable.com, to illustrate our approach: First, all metadata especially tags of mashups and APIs at Programmable.com are crawled and preprocessed by the suffix stripping algorithm to lower the noise. Second, a Mashup-Mashup Network (MMN) is constructed to represent the Mashups and their relationships. And the community detection technique in complex network theory is introduced to mine the community structures (the potential domains of these Mashups) in MMN. Based on the Mashup communities, we further group the tags into corresponding domains. Finally the tag ontology is built with reference to WordNet, and embedded in our own developed s oftware s ervice r egistry and r epository (S2R2), to improve the performance of service searching. Comprehensive experiments are also conduct to testify the effectiveness of the proposed approach.

MTag: A model to enable collaborative medical tagging in medical blogs

Abstract Collaborative tagging is the practice of collaboratively creating and managing tags to annotate and categorize online content. Current collaborative tagging activities within medical blogs are done using free words chosen by users. These tags are not based on standard medical terminologies. The resulted tags are inefficient in terms of medical meanings and semantic interlinking capabilities. In this paper, MTag is presented as a new model for collaborative tagging in medical blogs, i.e. tagging blog entries with medical information. MTag includes two modules: the service module and the semantic module. The service module enables health professionals provide blog posts with auto-completed tags that represent actual medical terms and categorize their tags. Tags are mapped to URIs from online medical knowledge datasets to clarify their medical meaning. At the same time, the semantic module is equipped with a tag ontology which extends the Social Semantic Cloud of Tags (SCOT) ontology to consent medical specifications of tags. Eventually, a prototype is developed to test the MTag’s two modules. The results show that both modules are working properly.

A New Method for Tag Ontology Extraction for Service

A New Method for Tag Ontology Extraction for Service

태그 질의 확장 기능에 기반한 비디오 검색 시스템의 효율성에 대한 실험적 연구

본 연구는 폭소노미가 비디오 자료를 색인하고 브라우징 하는데 얼마나 유용한지 살펴본 후, 동등어, 동의어 및 관련어를 활용한 질의 확장을 통해서 수행되는 폭소노미 태그 통제가 비디오 검색에 얼마나 효율적인지 조사해 보았다. 이를 위해서, 태그들을 태그 간의 동등 및 연관 관계에 기초하여 클러스터링하고 이러한 정보를 질의 확장에 적용시킨 실험 시스템을 설계, 구현하고 이러한 제안된 시스템이 정보검색 과정에서 폭소노미의 효율성을 얼마나 개선시킬 수 있는지에 대해서 실험을 통해서 확인해 보았다. 실험 결과, 질의 확장을 통해서 태그 통제를 한 제안된 시스템은 태그 통제를 전혀 하지 않은 시스템과 비교하여, 재현율은 증가하였으나 정확률은 전혀 차이가 없는 것으로 나타났다. 본 연구 결과는 폭소노미를 디지털 비디오 도서관의 소셜 메타데이터로 적용하기 위한 하나의 방안이 될 것으로 생각된다.

Semantic representation for copyright metadata of user‐generated content in folksonomies

PurposeThe purpose of this research is to investigate some general features of folksonomies and user‐generated content with copyright issues, and to present semantic representation for folksonomies using a tag ontology that can be used to represent tagging data at a semantic level using Semantic Web technologies.Design/methodology/approachAn exploratory study is described that features current social tagging methods and copyright metadata. In particular, a tag ontology is extended for representing copyright metadata across different platforms.FindingsThe main finding is that Social Semantic Cloud of Tags can improve the expressive knowledge representation of folksonomies and that this ontology can aid in describing copyright metadata using some extended properties.Originality/valueThe paper gives a valuable insight into representing folksonomies with Semantic Web technologies that enable the representation, exchange, and reuse of tagging data, and provides a way to reduce the risk of copyright infringements in the process of tag sharing in folksonomies.

Upper tag ontology for integrating social tagging data

AbstractData integration and mediation have become central concerns of information technology over the past few decades. With the advent of the Web and the rapid increases in the amount of data and the number of Web documents and users, researchers have focused on enhancing the interoperability of data through the development of metadata schemes. Other researchers have looked to the wealth of metadata generated by bookmarking sites on the Social Web. While several existing ontologies have capitalized on the semantics of metadata created by tagging activities, the Upper Tag Ontology (UTO) emphasizes the structure of tagging activities to facilitate modeling of tagging data and the integration of data from different bookmarking sites as well as the alignment of tagging ontologies. UTO is described and its utility in modeling, harvesting, integrating, searching, and analyzing data is demonstrated with metadata harvested from three major social tagging systems (Delicious, Flickr, and YouTube).

Perspectives on social tagging

AbstractSocial tagging is one of the major phenomena transforming the World Wide Web from a static platform into an actively shared information space. This paper addresses various aspects of social tagging, including different views on the nature of social tagging, how to make use of social tags, and how to bridge social tagging with other Web functionalities; it discusses the use of facets to facilitate browsing and searching of tagging data; and it presents an analogy between bibliometrics and tagometrics, arguing that established bibliometric methodologies can be applied to analyze tagging behavior on the Web. Based on the Upper Tag Ontology (UTO), a Web crawler was built to harvest tag data from Delicious, Flickr, and YouTube in September 2007. In total, 1.8 million objects, including bookmarks, photos, and videos, 3.1 million taggers, and 12.1 million tags were collected and analyzed. Some tagging patterns and variations are identified and discussed.

A URI is Worth a Thousand Tags

Although tagging is a widely accepted practice on the Social Web, it raises various issues like tags ambiguity and heterogeneity, as well as the lack of organization between tags. We believe that Semantic Web technologies can help solve many of these issues, especially considering the use of formal resources from the Web of Data in support of existing tagging systems and practices. In this article, we present the MOAT—Meaning Of A Tag—ontology and framework, which aims to achieve this goal. We will detail some motivations and benefits of the approach, both in an Enterprise 2.0 ecosystem and on the Web. As we will detail, our proposal is twofold: It helps solve the problems mentioned previously, and weaves user-generated content into the Web of Data, making it more efficiently interoperable and retrievable.

Search in Social Tagging Systems Using Ontological User Profiles

In this paper we present a modified hierarchical agglomerative clustering algorithm for building tag ontologies for social tagging systems. The modified algorithm first uses a clustering algorithm called Domain Similarity Clustering By Committee (DSCBC) (Tomuro et al. 2007) to derive a set of tag committees. We apply DSCBC to the tags entered by the users of social tagging systems and derive (un-ambiguous) committees of tags. Using the committees, a tag ontology is constructed in which an ambiguous tag is separated into multiple, disambiguated tags/nodes. Then a tag profile of a given user is matched against the ontology, and an ontological profile of the user is created. Finally a preference vector is fed into the (modified) FolkRank algorithm (Hotho et al. 2006a), and the web resources ordered based on the user's preferences are returned. We run our system on the data from two social tagging systems and compare the results with other algorithms. The results showed our algorithm achieved marked improvements over other algorithms.

P.5.076 Analysis of cerebrovascular andneuroprotective effects of afobazole

The social media microblogging service Twitter is gaining popularity in the field of urology as a fast and effective communication platform. We assessed volume, subject matter, influencers and content of urology related discussions on the Twitter platform using the recently proposed Urology Tag Ontology hashtag list.We queried the Symplur Signals database for tweet activity during a 1-year period. We used the Urology Tag Ontology hashtag list, comprised of 45 disease related hashtags in 9 urological subspecialties, to assess activity (numbers of tweets, users and impressions), users (geolocation, influencers) and content (words, tweet enhancements) of urology related Twitter traffic.Twitter activity during the study period included 334,642 tweets by 104,166 users with 1,397,107,305 impressions. Tweet activity varied among urological subspecialties and was largely dominated by urological oncology topics driven by #ProstateCancer. Users came from 224 countries and from all continents around the globe. Health care organizations accounted for the largest proportion of influencers (44%), followed by other individuals (22%) and physicians (13%). The top words were “prevent” (used 20,955 times), “cancer” (19,610), “follow” (19,169), “men” (19,165) and “condom” (18,425). The median (range) number of shares was 2,200 (1,414-8,854) for the top 10 links, 2,123 (1,878-2,737) for the top 10 retweets and 207 (12-438) for the top 10 photos.Twitter activity in the field of urology can be assessed using a standardized list of social media communication descriptors. The value of the Twitter communication platform is underscored by the large number of tweets and impressions in the urology space.