Leveraging Cross-Domain Social Media Analytics to Understand TV Topics Popularity

被引:8
|
作者
Pensa, Ruggero G. [1 ]
Sapino, Maria Luisa [1 ]
Schifanella, Claudio [2 ]
Vignaroli, Luca [2 ]
机构
[1] Univ Torino, Dept Comp Sci, Turin, Italy
[2] RAI CRIT, Turin, Italy
关键词
RETRIEVAL;
D O I
10.1109/MCI.2016.2572518
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
The way we watch television is changing with the introduction of attractive Web activities that move users away from TV to other media. The social multimedia and user-generated contents are dramatically changing all phases of the value chain of contents (production, distribution and consumption). We propose a concept-level integration framework in which users' activities on different social media are collectively represented, and possibly enriched with external knowledge, such as information extracted from the Electronic Program Guides, or available ontological domain knowledge. The integration framework has a knowledge graph as its core data model. It keeps track of active users, the television events they talk about, the concepts they mention in their activities, as well as different relationships existing among them. Temporal relationships are also captured to enable temporal analysis of the observed activity. The data model allows different types of analysis and the definition of global metrics in which the activity on different media concurs with the measure of success.
引用
收藏
页码:11 / 22
页数:12
相关论文
共 50 条
  • [1] Leveraging ParsBERT for cross-domain polarity sentiment classification of Persian social media comments
    Nigjeh, Mahnaz Panahandeh
    Ghanbari, Shirin
    MULTIMEDIA TOOLS AND APPLICATIONS, 2024, 83 (04) : 10677 - 10694
  • [2] Leveraging ParsBERT for cross-domain polarity sentiment classification of Persian social media comments
    Mahnaz Panahandeh Nigjeh
    Shirin Ghanbari
    Multimedia Tools and Applications, 2024, 83 : 10677 - 10694
  • [3] Towards Cross-Domain Learning for Social Video Popularity Prediction
    Roy, Suman Deb
    Mei, Tao
    Zeng, Wenjun
    Li, Shipeng
    IEEE TRANSACTIONS ON MULTIMEDIA, 2013, 15 (06) : 1255 - 1267
  • [4] Cross-Domain Spam Detection in Social Media: A Survey
    Dhaka, Deepali
    Mehrotra, Monica
    EMERGING TECHNOLOGIES IN COMPUTER ENGINEERING: MICROSERVICES IN BIG DATA ANALYTICS, 2019, 985 : 98 - 112
  • [5] Social Media Cross-Source and Cross-Domain Sentiment Classification
    Zola, Paola
    Cortez, Paulo
    Ragno, Costantino
    Brentari, Eugenio
    INTERNATIONAL JOURNAL OF INFORMATION TECHNOLOGY & DECISION MAKING, 2019, 18 (05) : 1469 - 1499
  • [6] Leveraging Social Media Analytics for Physicians
    Woo, Benjamin K. P.
    Lu, Hanson T.
    ACADEMIC MEDICINE, 2023, 98 (02) : 156 - 157
  • [7] Leveraging social media analytics for startups
    Dev, Jayati
    1600, Association for Computing Machinery (27): : 72 - 73
  • [8] Cross-Domain Depression Detection via Harvesting Social Media
    Shen, Tiancheng
    Jia, Jia
    Shen, Guangyao
    Feng, Fuli
    He, Xiangnan
    Luan, Huanbo
    Tang, Jie
    Tiropanis, Thanassis
    Chua, Tat-Seng
    Hall, Wendy
    PROCEEDINGS OF THE TWENTY-SEVENTH INTERNATIONAL JOINT CONFERENCE ON ARTIFICIAL INTELLIGENCE, 2018, : 1611 - 1617
  • [9] Cross-Domain Health Misinformation Detection on Indonesian Social Media
    Putri, Divi Galih Prasetyo
    Budi, Savitri Citra
    Syafiandini, Arida Ferti
    Amal, Ikhlasul
    Krisnandaru, Revandra Aryo Dwi
    INTERNATIONAL JOURNAL OF ADVANCED COMPUTER SCIENCE AND APPLICATIONS, 2025, 16 (01) : 1218 - 1224
  • [10] Cross-Domain Hashtag Recommendation and Story Revelation in Social Media
    Badami, Mahsa
    Nasraoui, Olfa
    2018 IEEE INTERNATIONAL CONFERENCE ON BIG DATA (BIG DATA), 2018, : 4294 - 4303