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A Novel Tweet Recommendation Framework for Twitter

2019 VOLUME-8 ISSUE-10, AUGUST 2019, REGULAR ISSUE  
As their social network increases it becomes challenging for them to find the relevant content from the massive collection of information.  ...  A Twitter user needs to scan a lot of less relevant posts to find the interesting tweets. Important updates may get lost if user is not able to read all the messages.  ...  Twitter users put hashtags in their tweets to categorize them in a way that makes it easy for other users to find and follow tweets about a specific topic.  ... 
doi:10.35940/ijitee.j1150.0881019 fatcat:schnyve3fbb4hfj6wdecm4uhge

Tweets Classification and Sentiment Analysis for Personalized Tweets Recommendation

Asad Masood Khattak, Rabia Batool, Fahad Ahmed Satti, Jamil Hussain, Wajahat Ali Khan, Adil Mehmood Khan, Bashir Hayat, Atif Khan
2020 Complexity  
Publicly available tweets are fetched and classified and sentiments expressed in tweets are extracted and normalized. This research uses domain-specific seed list to classify tweets.  ...  The proposed system was tested on a dataset of almost 1 million tweets and was able to classify up to 96% tweets accurately.  ...  Figure 1 : 1 Figure 1: e proposed system architecture for profiling and tweet recommendation. Figure 4 : 4 Figure 4: Sentiment analysis results for a diabetic person.  ... 
doi:10.1155/2020/8892552 fatcat:yc3kbq7vsbfadn5z6q2twtoxz4

Sentiment-aware personalized tweet recommendation through multimodal FFM

Ryosuke Harakawa, Daichi Takehara, Takahiro Ogawa, Miki Haseyama
2018 Multimedia tools and applications  
For realizing quick and accurate access to desired information and effective advertisements or election campaigns, personalized tweet recommendation is highly demanded.  ...  To overcome the limitation, a method for sentiment-aware personalized tweet recommendation through multimodal Field-aware Factorization Machines (FFM) is newly proposed in this paper.  ...  The final publication is available at "https://link.springer.com/article/10.1007/s11042-018-5876-x".  ... 
doi:10.1007/s11042-018-5876-x fatcat:hgkptz3iubfsrp4qj7z3geds3i

A Link Prediction Strategy for Personalized Tweet Recommendation through Doc2Vec Approach

Mojtaba Zahedi Amiri, Abdullah Shobi
2017 Research in Economics and Management  
there appear a main research subject to help users to find his/her interests among vast amount of relevant and irrelevant information.  ...  Recommender systems are helped to handle information overload problem and in this paper we introduce our Tweet Recommendation System that implement user's Twitter information (Tweets, Retweet, Like,...  ...  which model relevance between users and news articles using a mix of signals drawn from the news stream and from twitter: Profile of social neighborhood of the user, Content of their own tweet stream,  ... 
doi:10.22158/rem.v2n4p63 fatcat:xm5wq7d5qzbljhmfoiutaoulby

Teaching Tweeting: Recommendations for Teaching Social Media Work in LIS and MSIS Programs

Rachel N. Simons, Melissa G. Ocepek, Lecia J. Barker
2016 Journal of Education For Library and Information Science  
technical skills and the knowledge of specific platforms to be important, respondents also recommend that professionals be able to multi-task, work and update their knowledge independently, and adopt new  ...  Above all, respondents emphasized the high standards for social media communication and encouraged strong written communications skills, thus suggesting that MLIS and MSIS coursework should actively develop  ...  re-tweets for the campaign.  ... 
doi:10.3138/jelis.57.1.21 fatcat:vvka2dskxzetbawnza4ksnxp6i

Context-aware Image Tweet Modelling and Recommendation

Tao Chen, Xiangnan He, Min-Yen Kan
2016 Proceedings of the 2016 ACM on Multimedia Conference - MM '16  
To demonstrate the effectiveness our framework, we focus on the task of personalized image tweet recommendation, developing a feature-aware matrix factorization framework that encodes the contexts as a  ...  In this work, we enrich the representation of images in image tweets by considering their social context.  ...  We also would like to thank Yongfeng Zhang and Hanwang Zhang for their help and discussions.  ... 
doi:10.1145/2964284.2964291 dblp:conf/mm/ChenHK16 fatcat:nepnjdu5vbffbhrhkisac5p5fe

Making your interests follow you on twitter

Marco Pennacchiotti, Fabrizio Silvestri, Hossein Vahabi, Rossano Venturini
2012 Proceedings of the 21st ACM international conference on Information and knowledge management - CIKM '12  
In this paper we introduce the task of tweet recommendation, the problem of suggesting tweets that match a user's interests and likes.  ...  Our approach could be easily leveraged to build, for example, a Twitter or Facebook timeline that collects messages that are of interest for the user, but that are not posted by her friends.  ...  For instance, each of these two tweets "What's new in Linux 3.2? #linux"and"New features in Linux 3.2. #linux" may be highly interesting for a user but reporting both of them is useless.  ... 
doi:10.1145/2396761.2396786 dblp:conf/cikm/PennacchiottiSVV12 fatcat:3dmsvapbzbggzoyfj54pk5iope

Information Recommendation System Based on the Analysis of User Relationship and Micro- blogging Content Mining

F.W. Han
2016 Chemical Engineering Transactions  
On account of this, the thesis proposes another calculation method which is based on the user relationship and micro-blogging content analysis to make the Weibo information recommendation for centre audience  ...  Acknowledgment This paper is supported by the year in 2016, Nanjing Forest Police College, "The Fundamental Research Funds for the Central Universities". The project number is LGZD201601  ...  As for the emotional propensity analysis, the article uses the word activation force method to in-depth study relationship between the user's emotional words and topic terms and determine the relevant  ... 
doi:10.3303/cet1651096 doaj:c9c61dbef9bd40ff9cf5869c552bbe8b fatcat:tihm4n7m55dp3cdcy6kjuvewe4

Network-Aware Recommendations of Novel Tweets

Noor Aldeen Alawad, Aris Anagnostopoulos, Stefano Leonardi, Ida Mele, Fabrizio Silvestri
2016 Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval - SIGIR '16  
In this paper, we present a novel tweet-recommendation approach, which exploits network, content, and retweet analyses for making recommendations of tweets.  ...  Helping these users to discover potentially interesting tweets is an important task for such services.  ...  Acknowledgement We would like to thank the authors of [10] for having provided the code of their recommendation algorithm.  ... 
doi:10.1145/2911451.2914760 dblp:conf/sigir/AlawadALMS16 fatcat:34alhvjuqjf3zkax6ef24ersaq

How Twitter is Changing the Nature of Financial News Discovery

Mark Dredze, Prabhanjan Kambadur, Gary Kazantsev, Gideon Mann, Miles Osborne
2016 Proceedings of the Second International Workshop on Data Science for Macro-Modeling - DSMM'16  
Historically, financial news has been discovered through company press releases, required disclosures and news articles.  ...  We explain why today Twitter is a valuable source of material financial information and describe opportunities and challenges in using this novel news source for financial information discovery.  ...  While researchers have considered tweet recommendation systems [43, 44, 21, 1, 8] , it remains a nontrivial challenge to find the right tweet for the right person at the right time.  ... 
doi:10.1145/2951894.2951903 dblp:conf/cikm/DredzeKKMO16 fatcat:c3nbeutsnralfktskj7werqxpa

Toward Social Media Content Recommendation Integrated with Data Science and Machine Learning Approach for E-Learners

Zeinab Shahbazi, Yung Cheol Byun
2020 Symmetry  
The recommendations by the system are relevant tweets, popular relevant Twitter users, and research papers from DBLP.  ...  The developed project recommends relevant symmetric articles to e-learners from the social network of Twitter and the academic platform of DBLP.  ...  The user reads the first tweet if this tweet is relevant to the given keyword then the user marks this tweet as relevant or otherwise irrelevant. The user does the same steps for all tweets.  ... 
doi:10.3390/sym12111798 fatcat:wfgccritmjgn7lopmy7yz7dxna

User-Query Processing through Dynamic Tweets Status Recommender System

V. Kakulapati, D. Vasumathi, G. Suryanarayana
2021 Psychology (Savannah, Ga.)  
Through Twitter, users can find the relevant information on the search they perform, but understanding the past, present, and future information relevant to the investigation source is needed real-time  ...  the understanding of the tweet content, suggest the dynamic status of the tweets.  ...  And there become the user's new tweets, forming only the present user tweets with the new list.  ... 
doi:10.17762/pae.v58i1.2180 fatcat:pduqspkjmbcx5o6ccbz26emcoe

Mining Recipes in Microblog

Shengyu Liu, Qingcai Chen, Shanshan Guan, Xiaolong Wang, Huimiao Shi
2013 2013 International Conference on Asian Language Processing  
In the proposed method, snippets of text relevant to recipes are firstly extracted from Baidu Encyclopedia.  ...  After an examination on the candidate tweets, we find that almost all the candidate tweets are relevant to recipes.  ...  Tweets recommending health care foods; 2. Tweets listing foods that have the same health care effect; 3. Tweets describing the nutritional value of a particular food in detail; 4.  ... 
doi:10.1109/ialp.2013.13 dblp:conf/ialp/LiuCGWS13 fatcat:kxowtzkvb5ewlpbu3fwk4ttdpm

Classifying Twitter favorites: Like, bookmark, or Thanks?

Genevieve Gorrell, Kalina Bontcheva
2014 Journal of the Association for Information Science and Technology  
The focus of this article is on studying why and how Twitter users mark tweets as "favorites"-a functionality with currently poorly understood usage, but strong relevance for personalization and information  ...  Prior work has categorized Twitter users, as well as studied the use of lists and re-tweets and how these can be used to infer user profiles and interests.  ...  However, re-tweets are not only sparse data (only 6% of tweets get re-tweeted [Sysomos Inc, 2010] ), but also only account for certain kinds of tweet relevance and interestingness (Rout, Bontcheva, &  ... 
doi:10.1002/asi.23352 fatcat:ssnj6tswlrhundf3zm77mt5swy

A Survey of Recommender Systems in Twitter [chapter]

Su Mon Kywe, Ee-Peng Lim, Feida Zhu
2012 Lecture Notes in Computer Science  
Finally, it proposes a few research directions for recommendation tasks in Twitter.  ...  The paper therefore aims to fill this gap by introducing a taxonomy of recommendation tasks in Twitter, and to use the taxonomy to describe the relevant works in recent years.  ...  The paper uses spectrum entity extraction system [20] and applies the concept of entity to find the relatedness between tweets and news articles.  ... 
doi:10.1007/978-3-642-35386-4_31 fatcat:n7wdqfz6snbxbl2j7dmiabffsu
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