標(biāo)題: Titlebook: Big Data and Social Media Analytics; Trending Application Mehmet ?ak?rta?,Mehmet Kemal Ozdemir Book 2021 The Editor(s) (if applicable) and [打印本頁] 作者: ambulance 時(shí)間: 2025-3-21 16:52
書目名稱Big Data and Social Media Analytics影響因子(影響力)
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書目名稱Big Data and Social Media Analytics網(wǎng)絡(luò)公開度學(xué)科排名
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書目名稱Big Data and Social Media Analytics讀者反饋
書目名稱Big Data and Social Media Analytics讀者反饋學(xué)科排名
作者: Hla461 時(shí)間: 2025-3-21 22:27 作者: mettlesome 時(shí)間: 2025-3-22 03:04 作者: atopic-rhinitis 時(shí)間: 2025-3-22 06:56 作者: Prologue 時(shí)間: 2025-3-22 12:25 作者: Trabeculoplasty 時(shí)間: 2025-3-22 12:53 作者: Mechanics 時(shí)間: 2025-3-22 19:26
Advanced Evolutionary Algorithmser systems and social networks exhibit phenomena under which information for certain users or items is limited, such as the cold start and the grey sheep phenomena in collaborative filtering systems and the isolated users in social networks. In the context of a social network-aware collaborative fil作者: BUDGE 時(shí)間: 2025-3-22 22:09 作者: seroma 時(shí)間: 2025-3-23 05:13 作者: 承認(rèn) 時(shí)間: 2025-3-23 09:34 作者: 收養(yǎng) 時(shí)間: 2025-3-23 10:16 作者: 奇怪 時(shí)間: 2025-3-23 15:36
Introduction to Evolutionary Algorithms processing and machine learning, can play a vital role in mitigating this burden, especially with availability and real-time analyses of social media. One such application is ., intuitively defined as the semi-automatic assignment of one or more . labels (such as food, medicine or water) from a con作者: deciduous 時(shí)間: 2025-3-23 18:09 作者: braggadocio 時(shí)間: 2025-3-24 00:01 作者: obstinate 時(shí)間: 2025-3-24 04:42
Advanced Evolutionary Algorithmss such as Facebook, allows users to categorize tweets by the use of “hashtags”. Communication on Twitter can be mapped in terms of hashtag graphs, where vertices correspond to hashtags, and edges correspond to co-occurrences of hashtags within the same distinct tweet. Furthermore, a vertex in hashta作者: AUGUR 時(shí)間: 2025-3-24 10:21 作者: 反叛者 時(shí)間: 2025-3-24 14:28 作者: 我沒有命令 時(shí)間: 2025-3-24 17:45
2190-5428 t compression of large networks, link prediction in hashtag .This edited book provides techniques which address various aspects of big data collection and analysis from social media platforms and beyond. It covers efficient compression of large networks, link prediction in hashtag graphs, visual ex作者: 外形 時(shí)間: 2025-3-24 21:25 作者: 說明 時(shí)間: 2025-3-25 00:55 作者: 放肆的你 時(shí)間: 2025-3-25 07:16
Safe Travelling Period Recommendation to High Attack Risk European Destinations Based on Past Attacom the past years, which are widely available, and (2) developing an algorithm that recommends relatively safe periods to potential travellers..The results of this work will be useful for tourists, visitors, businesses and operators, as well as relevant stakeholders and actors.作者: 解凍 時(shí)間: 2025-3-25 10:01
Introduction to Evolutionary Algorithmsviding a bibliographic analysis of 31,763 network science papers, we construct the co-authorship network of 56,646 network scientists and we analyze its topology and dynamics. We shed light on the collaboration patterns of the last 20 years of network science by investigating numerous structural pro作者: needle 時(shí)間: 2025-3-25 12:23 作者: Directed 時(shí)間: 2025-3-25 19:14
Advanced Evolutionary Algorithmse report on our extensions on earlier works in this area which comprise of (1) the development of an algorithm for discovering the most reliable recommenders of a social network recommender system and (2) the development and evaluation of a new collaborative filtering algorithm that synthesizes the 作者: BUCK 時(shí)間: 2025-3-25 23:20 作者: 墊子 時(shí)間: 2025-3-26 00:25
Introduction to Evolutionary Algorithmsations, journalists, and political and social scientists to examine various cyber campaigns. There are a few challenges in blog data analysis. For instance, since blogs are not uniformly structured, the absence of a universal Application Programming Interface (API) makes it difficult to collect blog作者: landfill 時(shí)間: 2025-3-26 07:56 作者: GONG 時(shí)間: 2025-3-26 11:04 作者: debunk 時(shí)間: 2025-3-26 15:56 作者: 粉筆 時(shí)間: 2025-3-26 18:58 作者: 時(shí)代錯(cuò)誤 時(shí)間: 2025-3-27 00:57 作者: DEAWL 時(shí)間: 2025-3-27 01:36 作者: doxazosin 時(shí)間: 2025-3-27 06:22 作者: hemoglobin 時(shí)間: 2025-3-27 12:43 作者: 弄臟 時(shí)間: 2025-3-27 17:07
Analyzing Cyber Influence Campaigns on YouTube Using YouTubeTracker,ol can help identify leading actors, networks and spheres of influence, emerging popular trends, as well as user opinion. This analysis can also be used to understand user engagement and social networks. This can help reveal suspicious and inorganic behaviors (e.g., trolling, botting, commenter mobs作者: 離開就切除 時(shí)間: 2025-3-27 21:46
Blog Data Analytics Using Blogtrackers,ations, journalists, and political and social scientists to examine various cyber campaigns. There are a few challenges in blog data analysis. For instance, since blogs are not uniformly structured, the absence of a universal Application Programming Interface (API) makes it difficult to collect blog作者: 抒情短詩 時(shí)間: 2025-3-28 01:04 作者: 符合規(guī)定 時(shí)間: 2025-3-28 04:17 作者: amorphous 時(shí)間: 2025-3-28 08:32
Efficient and Flexible Compression of Very Sparse Networks of Big Data,llenging to find these frequently followed groups because most users are likely to follow only a small number of famous users. In this chapter, we present an efficient and flexible compression model for supporting the analysis and mining of very sparse networks of big data, from which the frequently作者: ADOPT 時(shí)間: 2025-3-28 13:07 作者: Ordeal 時(shí)間: 2025-3-28 17:23
Analysis of Link Prediction Algorithms in Hashtag Graphs,more popular hashtags have a higher probability to appear with other hashtags in the future. We then apply these improved methods to three sets of Twitter data with the intent of predicting hashtag co-occurrences in the future. In addition to these methods, we investigate the performance of a new, g作者: 急性 時(shí)間: 2025-3-28 19:21 作者: hermetic 時(shí)間: 2025-3-29 02:47
Twenty Years of Network Science: A Bibliographic and Co-authorship Network Analysis,y field called network science. Namely, these highly-cited seminal papers were written by Watts and Strogatz, Barabási and Albert, and Girvan and Newman on small-world networks, on scale-free networks and on the community structure of complex networks, respectively. In the past 20 years – due to the作者: meretricious 時(shí)間: 2025-3-29 05:47
Impact of Locational Factors on Business Ratings/Reviews: A Yelp and TripAdvisor Study,larly, Yelp, Trip Advisor, and Zomato are using a social media platform where users can share feedback, scores, photos, and make reservations. Business owners keep a close eye on these crowd-sourced indicators in order to maintain or improve their ratings. While improvements can be related to many f作者: 令人發(fā)膩 時(shí)間: 2025-3-29 07:29
,Identifying Reliable Recommenders in Users’ Collaborating Filtering and Social Neighbourhoods,er systems and social networks exhibit phenomena under which information for certain users or items is limited, such as the cold start and the grey sheep phenomena in collaborative filtering systems and the isolated users in social networks. In the context of a social network-aware collaborative fil作者: Mortar 時(shí)間: 2025-3-29 15:25
Safe Travelling Period Recommendation to High Attack Risk European Destinations Based on Past Attacential visitor will probably avoid travelling to a high attack risk country, due to safety reasons, hence will miss the opportunity to visit it, and, on the other hand, the country’s tourism will decline. This work addresses the aforementioned problem by (1) showing that relatively safe visiting per作者: 評論者 時(shí)間: 2025-3-29 17:43
Analyzing Cyber Influence Campaigns on YouTube Using YouTubeTracker, – almost one video per person worldwide. Because videos can deliver a complex message in a way that captures the audience’s attention more effectively than text-based platforms, it has become one of the most relevant platforms in the age of digital mass communication. This makes the analysis of You作者: 酷熱 時(shí)間: 2025-3-29 21:18
