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نتیجه جستجو - شبکه های اجتماعی

تعداد مقالات یافته شده: 593
ردیف عنوان نوع
1 Using social media photos and computer vision to assess cultural ecosystem services and landscape features in urban parks
استفاده از عکس های رسانه های اجتماعی و بینایی کامپیوتری برای ارزیابی خدمات اکوسیستم فرهنگی و ویژگی های چشم انداز در پارک های شهری-2022
Urban parks are important public places that provide an opportunity for city dwellers to interact with nature. In recent years, social media data have become a promising data source for the assessment of cultural ecosystem services (CES) and landscape features in urban parks. However, it is a challenging task to identify and classify the CES and landscape features from social media photos by manual content analysis. In addition, relatively few studies focused on the differences in landscape preferences between tourists and locals in urban parks. In this study, we used geotagged social media photos from Flickr and computer vision methods (scene recognition, image clustering and image labeling) based on the convolutional neural networks (CNN) and the Google Cloud Vision platform to assess the spatial preferences and landscape preferences (cultural ecosystem services and landscape features) of tourists and locals in the urban parks of Brussels. The spatial analysis results showed that the tourists’ photos were spatially concentrated on well-known parks located in the city center while the locals’ photos were rather spatially dispersed across all parks of the city. We identified 10 main landscape themes (corresponding to 4 CES categories and 10 landscape feature categories) from 20 image clusters by automated image analysis on social media photos. We also noticed that tourists paid more attention to the place identity featured by symbolic sculptures and buildings, while locals showed more interest in local species of plants, flowers, insects, birds, and animals. This research contributes to social media-based user preferences analysis and CES assessment, which could provide insights for urban park planning and tourism management.
keywords: داده های رسانه های اجتماعی | خدمات اکوسیستم فرهنگی | ویژگی های چشم انداز | پارک های شهری | بینایی کامپیوتر | Social media data | Cultural ecosystem services | Landscape features | Urban parks | Computer vision
مقاله انگلیسی
2 تحلیل شبکه اجتماعی: بررسی ارتباطات برای پیشرفت علم پرستاری نظامی
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 11 - تعداد صفحات فایل doc فارسی: 30
زمینه: دانشمندان پرستار نظامی در شاخه های وابسته به خدمات گنجانده شده اند (ارتش ، نیروی دریایی ، نیروی هوایی) با مأموریت های مختلف ، اما با هدف منحصر به فرد تولید و انتشار تحقیقات موثر بر سلامتی و رفاه ذینفعان وزارت دفاع.
هدف: این پروژه همکاری بین تحقیقات پرستاری TriService را بررسی می کند اعضای برنامه (TSNRP) ، به دنبال فرصت هایی برای تقویت ، متنوع سازی و گسترش همکاری تحقیقاتی هستند.
روش: تجزیه و تحلیل شبکه های اجتماعی (SNA) تحقیق تجربی از روابط بین بازیگران اجتماعی در سطوح مختلف تجزیه و تحلیل است . یک ارزیابی الکترونیکی SNA و نمونه برداری کلی برای بررسی همکاری های فعلی دانشمندان پرستار نظامی دکترای آماده (136 ( N= استفاده شد.
یافته ها: شبکه همکاری TSNRP دارای ساختار پیچیده خدمات محور است با بازیگران سطح بالا که دیگران به دنبال مشاوره ، دانش یا مهارت آنها هستند و به عنوان اتصالات یا پلهای مختلف در بین شعب خدمات فعالیت می کنند.
بحث: از نظر دانشمندان نظامی ، SNA در شناسایی افراد با نفوذ ، تجسم فرصت های مشاوره درون خدماتی ، طراحی سیاست های پاسخگو و جهت دهی فرصت های شغلی برای دانشمندان تازه کار نقش مهمی دارد.
کلید واژه ها: همکاری های حرفه ای دانشمندان پرستار | تحلیل شبکه اجتماعی | شبکه های اجتماعی | پرستاری نظامی | زمینه
مقاله ترجمه شده
3 Towards a pragmatic detection of unreliable accounts on social networks
به سوی تشخیص عملی حسابهای غیر قابل اعتماد در شبکه های اجتماعی-2021
In recent years, the problem of unreliable content in social networks has become a major threat, with a proven real-world impact in events like elections and pandemics, undermining democracy and trust in science, respectively. Research in this domain has focused not only on the content but also on the accounts that propagate it, with the bot detection task having been thoroughly studied. However, not all bot accounts work as unreliable content spreaders (p.e. bot for news aggregation), and not all human accounts are necessarily reliable. In this study, we try to distinguish unreliable from reliable accounts, independently of how they are operated. In addition, we work towards providing a methodology capable of coping with real-world situations by introducing the content available (restricting it by volume- and time-based batches) as a parameter of the methodology. Experiments conducted on a validation set with a different number of tweets per account provide evidence that our proposed solution produces an increase of up to 20% in performance when compared with traditional (individual) models and with cross-batch models (which perform better with different batches of tweets).
Keywords: Unreliable accounts detection | Social networks | Machine learning | Data mining | Volume and time adaptive methodology
مقاله انگلیسی
4 An analysis of Twitter users’ long term political view migration using cross-account data mining
تجزیه و تحلیل از مهاجرت دیدگاه های طولانی مدت کاربران توییتر با استفاده از داده های متقابل حسابداری-2021
During the 2016 US presidential election, we witnessed a polarized population and an election outcome that defied the predictions of many media sources. In this study, we conducted a follow-up on political view migration through tracking Twitter users’ account activity. The study was conducted by following a set of Twitter users over a four year period. Each year, Twitter user activities were collected and analyzed by our novel cross-account data mining algorithm. This algorithm through multiple iterations computes a numerical political score for each user based on their connection to other users and hashtags. We identified a set of seed users and hashtags using prominent political figures and movements to bootstrap the algorithm. The political score distribution demonstrates a divided population on political views. We also observed that users are more moderate in years close to elections (2017 and 2020) compared to years of none election (2018 and 2019). There is an overall migration trend from conservatives to progressives during the four years. This change in scores across the four year time frame suggests a unique political cycle exclusive to Donald Trump’s unprecedented presidential term. Our results in a broad sense portray the potential capabilities of a data collection and scoring algorithm that detected a noticeable political migration and describes the broad social characteristics of certain politically aligned users on social media platforms.
keywords: شبکه های اجتماعی | سیاست | توییتر | داده کاوی | Social networks | Politics | Twitter | Datamining
مقاله انگلیسی
5 Matching user accounts with spatio-temporal awareness across social networks
تطبیق حساب های کاربری با آگاهی مکانی-زمانی در سراسر شبکه های اجتماعی-2021
User identification aims at matching user accounts across social sites, which benefits many real-world applications. Existing works based on user trajectories usually address spatial and temporal data separately while not fully utilizing the coupling relation between them. Differently, in this work, we jointly consider spatialtemporal information in users’ acitvities to improve the user identification method. In particular, we observe that check-in records of different users tend to create inconsistent spatialtemporal information. These inconsistencies are useful for eliminating false user matching. Inspired by this observation, we propose a novel user identification method that captures the correlation of spatial and temporal information and the inconsistency in check-in records. It contains three main steps. 1) We measure the similarity of users’ trajectories based on a kernel density estimation, which considers spatial and temporal information simultaneously. 2) We assign a weight to each check-in record to favor discriminative ones. 3) We utilize the inconsistency among check-in records to compute penalties for trajectory similarity. The pair of accounts with higher similarity (than a predefined threshold) is then considered to be from the same user. We evaluate our approach on three ground-truth datasets. The results show that the proposed method offers competitive performance, with F1 values reaching 86.12%, 85.08% and 78.34%, which demonstrates the superiority of the proposed method over state-of-theart methods.
keywords: شناسه کاربر | آگاهی مکانی-زمانی | مطابقت با حساب های کاربری | داده های ورود | مسیر کاربر | User identification | Spatio-temporal awareness | Match user accounts | Check-in data | User trajectory
مقاله انگلیسی
6 نگاهی به خلاقیت: سوگیری های خلاقیت و تاثیرات متفاوت آنها بر عکس العمل هی مشتری در بازاریابی (نا)همزمان
سال انتشار: 2021 - تعداد صفحات فایل pdf انگلیسی: 17 - تعداد صفحات فایل doc فارسی: 26
چالش بازاریابی محتوی دیجیتالی ایجاد پیام های معنادار در لحظات معنادار است. بدین منظور، برندها اغلب پیام های رسانه اجتماعی را با لحظات موضوعی تنظیم می کنند که بازاریابی همزمان نام دارد. هدف بازاریابی همزمان ایجاد پیوند معنادار و توسعه خلاقیت آمیز در فشار زمانی به خاطر ماهیت همزمان بوده که می تواند تاثیر منفی بر تازگی و نوآوری داشته باشد. این تنش را با بررسی خلاقیت بازاریابی همزمان در اینستاگرام و پیامدهای آن بررسی نمودیم. طبق تحلیل محتوی 516 پیام اینستاگرام، به سوگیری معنادار برای بازاریابی همزمان پرداختیم و معناداری به بهای تازگی و پیشه وری تمامی می شود. به هر حال یافته های تحلیل محتوی و آزمایش مازاد نشان داد فقط پیشه وری و تازگی و نه معناداری تاثیر مثبت بر واکنش مصرف کننده داشتند.
کلمات کلیدی: شبکه های اجتماعی | بازاریابی در زمان واقعی | خلاقیت | سوگیری های خلاقیت | صنعتگری | اصالت | معنی دار بودن
مقاله ترجمه شده
7 A real-time deep-learning approach for filtering Arabic low-quality content and accounts on Twitter
یک رویکرد یادگیری عمیق در زمان واقعی برای فیلتر کردن عربی با کیفیت پایین محتوا و حساب های کاربری در توییتر-2021
Social networks have generated immense amounts of data that have been successfully utilized for research and business purposes. The approachability and immediacy of social media have also allowed ill-intentioned users to perform several harmful activities that include spamming, promoting, and phishing. These activities generate massive amounts of low-quality content that often exhibits duplicate, automated, inappropriate, or irrelevant content that subsequently affects users’ satisfaction and imposes a significant challenge for other social media-based systems. Several real-time systems were developed to tackle this problem by focusing on filtering a specific kind of low-quality content. In this paper, we present a fine-grained real-time classification approach to identify several types of lowquality tweets (i.e., phishing, promoting, and spam tweets) written in Arabic. The system automatically extracts textual features using deep learning techniques without relying on hand-crafted features that are often time-consuming to be obtained and are tailored for a single type of low-quality content. This paper also proposes a lightweight model that utilizes a subset of the textual features to identify spamming Twitter accounts in a real-time setting. The proposed methods are evaluated on a real-world dataset (40, 000 tweets and 1, 000 accounts), showing superior performance in both models with accuracy and F1-scores of 0.98. The proposed system classifies a tweet in less than five milliseconds and an account in less than a second.
keywords: محتوای کم کیفیت در شبکه های اجتماعی | حساب های اسپم | سیستم تشخیص زمان واقعی | تکنیک های یادگیری عمیق | Low-quality content in social networks | Spam accounts | Real-time detection system | Deep learning techniques
مقاله انگلیسی
8 Enterprise social network for knowledge sharing in MNCs: Examining the role of knowledge contributors and knowledge seekers for cross-country collaboration
شبکه اجتماعی شرکت اجتماعی برای به اشتراک گذاری دانش در MNCS: بررسی نقش مشارکتکنندگان دانش و دانش آموزان دانش برای همکاری متقابل کشور-2021
Online social networking within a large enterprise, known as enterprise social networking (ESN), is a critical requirement for social relationships and business-related informal discussions among its employees. ESN is important for multinational companies (MNCs) where employees work in different time zones in geographically dispersed locations in multiple continents. The MNCs use the ESN for their knowledge management and transfer activities among different subsidiaries in different countries or continents as a part of their strategic internationalization initiatives. ESN is developed by MNCs using enterprise social software for business or commercial knowledge management purposes and cross-country collaborations among their subsidiaries. ESN helps cross-country collaboration in MNCs to organize their internal communication (across different countries) and business discussions in an international environment. ESN is used mainly by two groups of employees in the MNCs: knowledge contributors and knowledge seekers. Both groups are essential for overall knowledge management strategy for creation, dissemination, and con- sumption of knowledge across countries. In this context, the purpose of this study is to examine the role of knowledge contributors and knowledge seekers in the MNCs using ESN for cross- country collaboration.
keywords: شبکه اجتماعی شرکت | مشارکت کنندگان دانش | دانش آموزان | mncs | همکاری متقابل کشور | Enterprise social network | Knowledge contributors | Knowledge seekers | MNCs | Cross-country collaboration
مقاله انگلیسی
9 Role of big data and social media analytics for business to business sustainability_ A participatory web context
Role of big data and social media analytics for business to business sustainability_ A participatory web context-2020
The digital transformation is an accumulation of various digital advancements, such as the transformation of the web phenomenon. The participatory web that allows for active user engagement and gather intelligence has been widely recognised as a value add tool by organisations of all shapes and sizes to improve business productivity and efficiency. However, its ability to facilitate sustainable business-to-business (B2B) activities has lacked focus in the business and management literature to date. This qualitative research is exploratory in nature and fills this gap through findings arising from interviews of managers and by developing taxonomies that highlight the capability of participatory web over passive web to enable different firms to engage in business operations. For this purpose, two important interrelated functions of business i.e. operations and marketing have been mapped against three dimensions of sustainability. Consequently, this research demonstrates the ability of big data and social media analytics within a participatory web environment to enable B2B organisations to become profitable and remain sustainable through strategic operations and marketing related business activities. The research findings will be useful for both academics and managers who are interested in understanding and further developing the business use of participatory web tools to achieve business sustainability. Hence, this may be considered as a distinct way of attaining sustainability.
Keywords: Participatory web | Marketing and operations | Big data | Social media analytics | Business sustainability | Business-to-business (B2B)
مقاله انگلیسی
10 Fostering Corporate Entrepreneurship with the use of social media tools
پرورش کارآفرینی شرکتی با استفاده از ابزارهای رسانه های اجتماعی-2020
The strategic use of Social Media can leverage innovation, relationships with customers, and the entrepreneurial orientation of the firm, as it provides useful knowledge to find new opportunities for innovation. Despite the relevance of this phenomenon to current hyper-competitive environments, empirical research on the topic re- mains scarce. To advance knowledge of this issue, the main purpose of the paper is to examine how Social Media use impacts the different dimensions of Corporate Entrepreneurship. Building on a sample of 201 technological firms, findings confirm that the use of Social Media tools impacted all dimensions of Corporate Entrepreneurship and enhanced firm performance. This paper contributes to the literature by empirically confirming how Social Media use helps to create business value. The study results also have important implications for managers, as they show the pathway managers must follow to harness the benefits of Social Media use to become more entrepreneurial.
Keywords: Social Media | Corporate Entrepreneurship | Organizational performance | Technology sector
مقاله انگلیسی
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