Show/Hide Menu
Hide/Show Apps
Logout
Türkçe
Türkçe
Search
Search
Login
Login
OpenMETU
OpenMETU
About
About
Open Science Policy
Open Science Policy
Open Access Guideline
Open Access Guideline
Postgraduate Thesis Guideline
Postgraduate Thesis Guideline
Communities & Collections
Communities & Collections
Help
Help
Frequently Asked Questions
Frequently Asked Questions
Guides
Guides
Thesis submission
Thesis submission
MS without thesis term project submission
MS without thesis term project submission
Publication submission with DOI
Publication submission with DOI
Publication submission
Publication submission
Supporting Information
Supporting Information
General Information
General Information
Copyright, Embargo and License
Copyright, Embargo and License
Contact us
Contact us
Context Based Semantic Relations in Tweets
Date
2014-01-01
Author
Özer, Özdikiş
Karagöz, Pınar
Oğuztüzün, Mehmet Halit Seyfullah
Metadata
Show full item record
Item Usage Stats
230
views
0
downloads
Cite This
Twitter, a popular social networking platform, provides a medium for people to share information and opinions with their followers. In such a medium, a flash event finds an immediate response. However, one concept may be expressed in many different ways. Because of users’ different writing conventions, acronym usages, language differences, and spelling mistakes, there may be variations in the content of postings even if they are about the same event. Analyzing semantic relationships and detecting these variations have several use cases, such as event detection, and making recommendations to users while they are posting tweets. In this work, we apply semantic relationship analysis methods based on term co-occurrences in tweets, and evaluate their effect on detection of daily events from Twitter. The results indicate higher accuracy in clustering, earlier event detection and more refined event clusters.
URI
https://hdl.handle.net/11511/86378
https://www.researchgate.net/publication/300706249_Context_Based_Semantic_Relations_in_Tweets
Relation
State of the Art Applications of Social Network Analysis
Collections
Department of Computer Engineering, Book / Book chapter
Suggestions
OpenMETU
Core
FACT EXTRACTION AND VERIFICATION PIPELINE FOR COVID-19 RELATED USER POSTS IN SOCIAL MEDIA
Temiz, Orkun; Taşkaya Temizel, Tuğba; Department of Bioinformatics (2022-6-29)
Social media has become a prevalent platform for consuming and sharing information online. The vast amounts of information, shared easily and rapidly by social media, have increased the demand for fact-checking. Misinformation threatens not only the reputation of individuals and organizations but also society. When the COVID-19 pandemic broke out, the concerns around misinformation, which threatens public health and society, have significantly increased. In this thesis, a new zero-shot fact extraction and v...
Context aware friend recommendation for location based social networks using random walk
Bağcı, Hakan; Karagöz, Pınar (null; 2016-04-10)
The location-based social networks (LBSN) facilitate users to check-in their current location and share it with other users. The accumulated check-in data can be employed for the benefit of users by providing personalized recommendations. In this paper, we propose a random walk based context-aware friend recommendation algorithm (RWCFR). RWCFR considers the current context (i.e. current social relations, personal preferences and current location) of the user to provide personalized recommendations. Our LBSN...
Combining topology-based & content-based analysis for followee recommendation on Twitter
Yanar, Aysu; Karagöz, Pınar; Taşkaya Temizel, Tuğba; Department of Information Systems (2015)
Twitter has become an important social platform for individuals and people share a high number of information about their personal lives, interests and viral news during emergencies. As of 2014, Twitter has 240 million active users and approximately 500 million tweets are shared every day. This information overload in Twitter has become a serious problem due to the growing volume of messages and increasing number of users. Recommender systems help to overcome this challenge. Finding interesting users and ge...
Determining user types from twitter account contentand structure
Gürlek, Mesut; Toroslu, İsmail Hakkı; Department of Computer Engineering (2021-3-05)
People are using social media platforms more and more every day; hence, they are be-coming suitable for research studies by their rich content. Twitter is one of the biggestand most widely used social media platforms, and many studies focus on Twitter forsocial media research. In this thesis, we propose methodologies for determining usertypes of Twitter accounts by their metadata, content, and structure. Our first problemis classifying organization vs. individual account types using only metadata. After weg...
INVESTIGATING THE INDIVIDUALS' PERCEPTION ABOUT SOCIAL MEDIA INFLUENCERS: A SURVEY STUDY ON UNIVERSITY STUDENTS
Yüksel, Umutcan Sümeyye; Özdemir, Özlem; Department of Business Administration (2022-9)
Internet and social media have become integral to our lives, creating social media celebrities or influencer terms. This thesis explores social media influencers' effects on social media users. Perceived similarity by the user to the influencer, wishful identification by the user with the influencer, perceived credibility of the influencer, and parasocial identification between the user and the influencer are investigated. This thesis aims to contribute to the literature by simultaneously analyzing perceive...
Citation Formats
IEEE
ACM
APA
CHICAGO
MLA
BibTeX
Ö. Özer, P. Karagöz, and M. H. S. Oğuztüzün,
Context Based Semantic Relations in Tweets
. 2014, p. 52.