Habibollah Salarzehi; Golbahar Pouranjenar; Amin Shakibai; Hassan Ghaffari
Abstract
The current research was conducted with the aim of identifying the effective drivers for the development of virtual social networks in identifying entrepreneurial opportunities. Virtual social networks, as a network of human communication, include WhatsApp, Instagram, Google Plus, LinkedIn, Facebook, ...
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The current research was conducted with the aim of identifying the effective drivers for the development of virtual social networks in identifying entrepreneurial opportunities. Virtual social networks, as a network of human communication, include WhatsApp, Instagram, Google Plus, LinkedIn, Facebook, Twitter and other platforms that include many opportunities in the field of entrepreneurship. The research was applied in terms of its purpose, and in terms of the nature and method of data collection, it was analytical-exploratory and of a mixed approach, in which Content analysis method was used in the qualitative part, and the MicMac method was used in the quantitative part. The intended sample in the qualitative section includes 9 experts, and in the quantitative section, it includes 20 experts who are proficient in the subject, who were selected by snowball sampling. The method of data collection in the qualitative part included library studies and interviews, and in the quantitative part it included the MicMac questionnaire. At the stage of library studies and interviews, 18 primary variables were identified, and 16 variables were used for quantitative analysis by adjusting the opinions of experts. After analyzing the data obtained from the MicMac questionnaire, 10 variables were determined as effective drivers. The results show that the most effective factor include; The size of virtual social networks and the presence of business contacts in virtual social networks and the least effective variable include; Transfer of information and existence of information resources in virtual social network.
Fatemeh Abbasi; Ameneh Khadivar; Mohsen Yazdinejad
Abstract
Nowadays, people use others' opinions on social networks for decision-making to purchase online products and services. Likewise, the companies which offer the products employ sentiment analysis of opinions of users and customers to adopt informed decisions and offer new products. Considering the ...
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Nowadays, people use others' opinions on social networks for decision-making to purchase online products and services. Likewise, the companies which offer the products employ sentiment analysis of opinions of users and customers to adopt informed decisions and offer new products. Considering the high volume of the contextual data, conversion, and analysis of such data is a major challenge in e-commerce. Sentiment analysis is a modern approach in the extraction of opinions. The obtained information from sentiment analysis can have a considerable impact on the efficient selection of customers. In the present study, a model has been proposed for sentiment analysis of users' opinions for buying a cell phone in Digikala. This study is applicable to the objective aspect. The data includes users' opinions in Digikala. The statistical sample consists of opinions of cell phone users in Digikala. Supervised learning, as well as Python package, were utilized for analysis and implementation. A model has been proposed for sentiment analysis of users' opinions. The results demonstrate that this model can classify users' opinions with an accuracy equal to 0.892. Similarly, the results reveal that users' opinions about ease of use, possibilities, and capabilities of the cell phone are positive and about purchase value to price, innovation, design and appearance, and quality of cell phones are negative. The proposed model can be implemented in e-commerce websites like Digikala and its output can be observed by users systematically. Finally, it can be led to inform decision-making for buyers and companies which offer products.
Negarsadat Mesbahi Jahromi ; Vahidreza Mirabi; Serajeddin Mohebbi ; Mehdi Bagheri
Abstract
The share of social commerce in Iran is relatively small compared to the developed countries in the field of social commerce. So, it important to identify factors which are critical in the implementation of social commerce. The main purpose of this research is to identify legal and behavioral gaps on ...
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The share of social commerce in Iran is relatively small compared to the developed countries in the field of social commerce. So, it important to identify factors which are critical in the implementation of social commerce. The main purpose of this research is to identify legal and behavioral gaps on the implementation of social commerce among the startups. The statistical population in the qualitative section consists of social commerce experts in knowledge-based companies in the field of information technology in the science and technology park of Tehran University. Experts were identified using snowball and judgmental sampling techniques. According to the adequacy of data, 20 interviews were performed in total. The statistical population in the quantitative section consisted of the managers of startup companies located in Tehran. Two-step sampling method was used to determine the sample size. Data in qualitative section were collected through deep interviews and in the quantitative section it was collected through questionnaires. Data was analyzed using SmartPLS2 software in quantitative section. The results show that changes in business environment is as causal conditions. The pivotal phenomenon including: the implementation of social commerce, the contextual conditions including the business cultures and legal gaps, the interfering conditions including the behavioral gaps, and business resource conditions, and strategies including the reliability of online markets and the development of technical infrastructure have been identified. Ultimately, the consequences of this study have been enhancing business ease and improving sales performance.
Rohulla Kosari Langari; Soheila Sardar; Seyed Abdollah Amin Mousavi; Reza Radfar
Abstract
Nowadays the growth in the use of social networks among different classes of world community is increasingly undeniable. Social networks database include Rich and valuable resources whose release and analysis with the purpose of marketing, publicity, National Security, Health and etc. can benefit researchers ...
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Nowadays the growth in the use of social networks among different classes of world community is increasingly undeniable. Social networks database include Rich and valuable resources whose release and analysis with the purpose of marketing, publicity, National Security, Health and etc. can benefit researchers of public and private institutions. But respect the privacy of the entities whose information is available to data miner analysis is essential as a legal protocol. In this Paper, through qualitative methodology Meta synthesis, all related dimensions, indicators and codes were identified and then the importance and priority of each of the factors was determined. Subsequently, the improved model of anonymity was presented by an optimizing firefly algorithm and fuzzy clustering. The result of simulation and assessment of the proposed model on the data of four social networks such as Facebook, YouTube, Twitter and Google+ depicts that privacy preserving of data with the lowest distortion ratio and the more usefulness of data.
Zohreh Dehdashti Shahrokh; vahid Nasehifar; Vahid Khashei; Mitra r Daneshparvar
Abstract
Nowadays, some customers tend to buy clothes through social networks, and several factors affect this willingness. One of the important factors influencing people's willingness to buy clothing through social networks is social and cultural factors. Hence, this research seeks to examine the role ...
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Nowadays, some customers tend to buy clothes through social networks, and several factors affect this willingness. One of the important factors influencing people's willingness to buy clothing through social networks is social and cultural factors. Hence, this research seeks to examine the role of social and cultural factors in the purchase of clothing through social networks. In this research, a mixed method has been used. In the qualitative section, texts were transcribed and coded through literature reviews and interviews with active vendors in social networks. The components were categorized into 4 final categories and then presented in the original model. In the quantitative part, based on the original model, a questionnaire was prepared and distributed among 385 apparel buyers in the networks. For data analysis, structural equation method and to examine the mediating role, Sobel test were used. The results showed that friends' recommendations, affirmation of others, and social conditions have a significant effect on the trust of individuals in social networks, and the trust of individuals has a significant effect on the consumer's willingness to buy clothing through social networks.
Abdol Majid Imani; Azam Hosseinifar; Moslem Mobaraki
Abstract
According to in today's competitive world, in addition to economic factors, social factors also can affect businesses and social networks as a social characteristic, the driving force and basis for social cohesion in business activities online role important. The purpose of this paper is to examine the ...
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According to in today's competitive world, in addition to economic factors, social factors also can affect businesses and social networks as a social characteristic, the driving force and basis for social cohesion in business activities online role important. The purpose of this paper is to examine the impact of social networking (content of social relations, the structure of social ties, community resource information, mode of data transfer) in digital entrepreneurship development (opportunity analysis, creation and website development, e-marketing application, implementation and development of e-commerce) have been investigated. The research population consisted of 70 managers and IT experts of knowledge societies based in Kerman province of science and technology. By collecting questionnaires, 35 questionnaires were selected as samples The research method in terms of nature, correlation and data analysis software (Spss) and SEM (Smart pls) is used. The results show that social networks has a significant positive impact on the development of digital entrepreneurship and the dimensions of social networks, content, social relations, ways of transmission of information, social information resource has the greatest impact on digital entrepreneurship.
Parvin Fakhri; Mahdi Hosseinzadeh Zadeh
Abstract
2016 USA presidential election results surprised many in America. Most experts and traditional polls had predicted that Hillary Clinton won election but results marked otherwise. In this study, with social network analysis method in content analysis approach, the election campaigns for the two main candidates ...
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2016 USA presidential election results surprised many in America. Most experts and traditional polls had predicted that Hillary Clinton won election but results marked otherwise. In this study, with social network analysis method in content analysis approach, the election campaigns for the two main candidates was investigated on the basis of tweets sent on Twitter platform during the three day period prior to November 8, 2016.It was found that in most analytical aspects such as analyzing tweets, retweets, hashtags, mentions words, user profiles and so on, Trump’s campaign advantage is evident and among users with a neutral trend Trump tendency is likely to dominate. In addition, we identify Some electoral strategies and effective political movements, for example, we understand that Clinton campaign focused on attacking Trump and vice versa Trump campaign focused on support Trump, or users, particularly neutral have shown particular attention to Wiki Leaks and disclosure of emails.
Seyed Mohammadbagher Jafari; Asef Karimi; Zahede i Abarghou
Abstract
رSocial networks are a new generation of social relationship area that despite short lifetime, have been able to play an important role in people’s life.Given the importance and presence of social networks in today lives and growing their influence and impact, understanding of user behavior patterns ...
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رSocial networks are a new generation of social relationship area that despite short lifetime, have been able to play an important role in people’s life.Given the importance and presence of social networks in today lives and growing their influence and impact, understanding of user behavior patterns has become interesting subjects of researches. The aim of this study is to investigate the factors affecting on continuance intention to use online social network websites and LinkedIn was chosen as a specialized social network in this research. The population was all of Iranian members of LinkedIn. The random available sampling was used and 352 questionnaires were collected and analyzed. The hypotheses were tested with using structural equation modeling. After variable factor analysis and the relations between variables and their impact on each other were examined through path analysis. Social effects, content, value, ease of use, the tie strength and satisfaction from social networks have been identified as factors affecting on continuance intention to use of social network websites. Meanwhile the satisfaction with higher path coefficient has a stronger impact than other factorsSocial networks are a new generation of social relationship area that despite short lifetime, have been able to play an important role in people’s life.Given the importance and presence of social networks in today lives and growing their influence and impact, understanding of user behavior patterns has become interesting subjects of researches. The aim of this study is to investigate the factors affecting on continuance intention to use online social network websites and LinkedIn was chosen as a specialized social network in this research. The population was all of Iranian members of LinkedIn. The random available sampling was used and 352 questionnaires were collected and analyzed. The hypotheses were tested with using structural equation modeling. After variable factor analysis and the relations between variables and their impact on each other were examined through path analysis. Social effects, content, value, ease of use, the tie strength and satisfaction from social networks have been identified as factors affecting on continuance intention to use of social network websites. Meanwhile the satisfaction with higher path coefficient has a stronger impact than other factors
