social media optimization

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Conversation driven Social Media Optimization :
Tactic and Effects on User Engagement

Conversation driven Social Media Optimization : Tactic and Effects on User Engagement

Creating engaging social media content remains the biggest challenge in digital marketing. Lack of framework and user-centric approach may contribute to campaign‘s ineffectiveness in fostering user engagement. This research introduces Conversation-driven Social Media Optimization (SMO), a two- steps tactic as the solution. Twitter was used as the media, and Indonesian tourism was used as the context. In Conversation Mining and Analysis step, optimized words from the most popular (―Temple‖ topic) and least popular conversation (―Surfing‖ topic) in Twitter were gauged. Later, were used to construct digital contents (listicle, photo gallery, videos) in the Conversation Steering step. Evaluative experiment revealed that using the tactic in content creation has significant effect on user engagement, most importantly word-of-mouth intention. Enthusiasm to travel moderated the effects. Yet, the effect does not depend on inherent engaging level of the content. Lastly, video with optimized words from most popular conversation was proven to the most effective content.
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Spotting and Removing Fake Product Review in Consumer Rating Reviews

Spotting and Removing Fake Product Review in Consumer Rating Reviews

Many people require review about a product before spending their money on the product. People may come across various reviews in the website but these reviews are genuine or fake is not identified by the user. In some review websites some good reviews are added by the product company people itself in order to make product famous this people belong to Social Media Optimization team. Every one give good reviews for many different products manufactured by their own firm. User will don’t know to find out whether the review is genuine or fake. To find out fake review this system is introduced. This system will find out fake reviews made by the social media optimization team by identifying the IP address. User will login to the system using user id and password and will view various products and will give review about the product. And the user will get genuine reviews about product. And while reviewing user needs to enter the email id from which he is reviewing and it would be verified. If user writes a fake review, then user id will be blocked and not allowing him to share his opinions again.
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Spotting and Removing Fake Product Review in Consumer Rating Reviews

Spotting and Removing Fake Product Review in Consumer Rating Reviews

Many people require review about a product before spending their money on the product. People may come across various reviews in the website but these reviews are genuine or fake is not identified by the user. In some review websites some good reviews are added by the product company people itself in order to make product famous this people belong to Social Media Optimization team. Every one give good reviews for many different products manufactured by their own firm. User will don’t know to find out whether the review is genuine or fake. To find out fake review this system is introduced. This system will find out fake reviews made by the social media optimization team by identifying the IP address. User will login to the system using user id and password and will view various products and will give review about the product. And the user will get genuine reviews about product. And while reviewing user needs to enter the email id from which he is reviewing and it would be verified. If user writes a fake review, then user id will be blocked and not allowing him to share his opinions again.
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Heuristics For Testing Steps Of The General Search Engine Optimization Process

Heuristics For Testing Steps Of The General Search Engine Optimization Process

Social media optimization is outlined by the distribution of social objects and their ability to rise to the highest of any connected search question, wherever and once it’s performed [2]. SMO encourages social media engagement and content sharing through the leading social networking sites that represent users learning and analysis environments [5]. Here are some general pointers for social media optimization: make certain on clicking variety button. User ought to be re-directed to the corresponding Facebook page, User ought to ready to just like the page. Make certain the quantity of likes gets incremented. Make certain once feeling that activity is obtaining displayed on user's profile page. Make certain the user is in a position to in contrast to the page. Check the quantity of likes gets decremented or not. Make certain on clicking the twitter button user gets directed to the twitter's page, User is in a position to share that page or tweet it. Check the count gets incremented by clicking on the twitter button. Make certain on clicking the Google and button, user is re-directed to the corresponding Google page and by language in user are ready to share page. Make certain by sharing, the forecast the Google and button will increase. Check if the positioning is shared with social media sites or not.
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Securing Image Transfer In Social Media

Securing Image Transfer In Social Media

Web-based social networks (WBSNs) are online communities where participants can establish the relationships and can be able to share resources across the Web with other users. In recent years, many of the WBSNs have been adopting Semantic Web technologies, such as FOAF, for representing users’ data and relationships, making it possible to enforce information interchange across multiple WBSNs. Despite its advantages in terms of information diffusion, this raised the need of giving content owners more control on the distribution of their resources, which may be accessed by a community far wider than expected. This paper presents a system that has an access control model for WBSNs, where in the policies are expressed as constraints on the type, depth, and trust level of existing relationships. Relevant features of our model are the use of certificates for granting relationships’ authenticity, and the client-side enforcement of access control according to a rule-based approach, where a subject requesting to access an object should demonstrate that it has the rights of doing that. Web-based social networks (WBSNs) are online communities that allow Web users to publish resources and to establish relationships with other users, possibly of different type for various purposes that has concerns as entertainment, religion, dating, or business. One of the recent trends in WBSNs is the adoption of Semantic Web technologies, in particular FOAF, to represent users’ personal data and relationships. Thanks to this and to the adoption of decentralized authentication systems like the OpenID, it has been made simpler to access and disseminate information across multiple WBSNs. If this has been quite a relevant improvement with respect to the previous situation, it is now necessary
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Social Media

Social Media

For this project I definitely had a lot of ideas floating around in my head but I struggled to get them down on paper. I think because I have a lot of opinions on this topic that criticize many of my peers, it made me want to say what was on my mind but I wanted to say it well. This was a great paper to write because social media is a topic that is so relatable to people my age. This made it so interesting to read articles and talk about social media usage. This paper really made me think about how people I know use social media and how I use it, and I realized that I don't just want to be another profile.
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Social Media Sentiment Analysis using Machine Learning and Optimization Techniques

Social Media Sentiment Analysis using Machine Learning and Optimization Techniques

. To carry out reduction in dimension the authors combined the Principle Component Analysis with SVM. Martineau and Finin. [5] Proposed a technique called Delta TFIDF which measure word scores efficiently before classification. Delta TFIDF was easy to understand, implement and compute. For sentiment classification the authors used support vector machines to achieve better accuracy with Delta TFIDF and using data sets of movie reviews. The authors said that Delta TFIDF is better than TDFIF feature and count term raw for all sizes of documents that weights for congressional detecting support for bill, sentiment polarity classification and subjectivity detection. The authors stated Delta TFIDF is first measuring approach to boost and identify the relevance of selective words using the calculated unsupervised distribution of features before classification between the two classes. Mohammad et al. [6] developed two SVM classifiers, one is term level task which determines the sentiment of a word in the message and one is message level task which determines the sentiment of messages such as SMS and tweets. The authors took part in a competition where 44 teams came in their submissions stood fist in work on tweets, getting 88.93 F-core in term-level task and 69.02 F-score in message-level task. The authors executed sentiment, semantic and surface- form features. The authors also produced two big term- sentiment associations, first with emoticons from tweets and second with sentiment –term hashtags from tweets. Neri et al. [7] performed sentiment analysis on newscast over more than 1000 Facebook posts and then compared the sentiment for dynamic company La7 and Rai – the Italian social broadcasting company which is emerging company. The authors observations were mapped with the study conducted by the Italian research institute highly specialized in study of media at empirical and theoretical level, occupied in the study of communication of politics in the mass media known as Osservatorio di Pavia. The authors experiment done by Knowledge Mining System which is used by security related
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Why customers intend to co create on Facebook in the case of customer engagement

Why customers intend to co create on Facebook in the case of customer engagement

However, while Lee and Kim (2018) did not use Customer Engagement as a possible predictor, this study did and found it to be of importance. While one can argue that meaning and concern are similar to benefits or a sort of gratification, Factor Analysis shows that gratification and Customer Engagement are indeed different constructs. Moreover, Discriminant Validity (Appendix D) was established showing that Customer Engagement and Hedonic Benefits are two different constructs. There are some differences between this study and that by Lee and Kim (2018). Their study location was South-Korea and this survey took place in Europe. While this study focussed on why people would intend to Co-create on Facebook itself, their study was on Corporate Social Networking Sites among people that already do Co-create. While these differences may explain some divergence in results, it appears that Customer Engagement is a predictor for Co-creation. Besides that, Hedonic Benefits seem to explain most of the expected gratification by itself.
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Social Media: Marketing For Generation Next

Social Media: Marketing For Generation Next

The growth and expansion of social media and its role in marketing is very effective for businesses. A company uses communities, social networks, blog marketing and more. It is the latest “buzz” and is now in trend. Large numbers of companies have their presence on social media marketing platform and they utilize them with innovative ideas to effectively maximize and globalize their campaign with social media marketing.

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Utilization of social media by politicians padang city

Utilization of social media by politicians padang city

Third, a combination of various features or facilities is a factor that causes the facebook social media effective as communication media and political campaigns in grabbing the public support. Pages, photo-video sharing, groups, messages, games and ads are the features or amenities are valuable facebook is in the process of communication and political campaigns (Nasrullah, 2015:128). Apart from the spectacular against the reality of the existence of facebook, it is interesting to open for discussion is the utilization of facebook as a communication channel. According to reports from a Bureau researcher Netherlands. Berenschot, nearly half the local party Netherlands using social media (primarily facebook) in the face of the elections of 2012 (www.kompas.com, accessed 2 April 2016 Saturday 22.00 hours). Research results Afdal Makkuraga Son who concluded that all the candidates in the Banten Pemilukada 2011 has been utilizing social media such as Facebook and Twitter in the vision and mission inform each (UMN, Volume III, number 2 December 2011, p23-32). The research of Neza Aninda Mirza (2014) stating that the role of facebook for beginners is the voters as a means of finding information about political parties and presidential candidates (Journal of Atmajaya University Yogyakarta, 2014). The next issue of the utilization of social media in the two countries United States and United Kingdom in shaping society's political behavior. Magdalena Saldana (IJOC, 2015:2015, vol. 9 p3304-3326) examines how the use of traditional media and the use of social media for news of political engagement impact citizens in both countries.
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Understanding of Social Media - History & Imp...

Understanding of Social Media - History & Imp...

Specifically, in the Indian context, social media has a vast scope of survival and growth. Here social has already become extremely popular and familiar; people are making its use in the field of marketing, branding, social interactions, research, campaigning, awareness, and even for political purposes too. It has enabled the commercial world to reach across the globe, and no business can afford to ignore it. Even at the social level, people are reaching out and apparently; they would not want to go back to the world of hindered connections. What is required is to utilize the credibility of social media wisely.
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Nationalism, Populism and Global Social Media

Nationalism, Populism and Global Social Media

financial incentives to read messages from people or organiza- tions with opposing views. It is possible that Twitter users may simply ignore such counterattitudinal messages in the absence of such incentives. Perhaps the most important limitation of our study is that we were unable to identify the precise mechanism that created the backfire effect among Republican respondents reported above. Future studies are thus urgently needed not only to determine whether our findings replicate in different popula- tions or within varied social settings but to further identify the precise causal pathways that create backfire effects more broadly. Future studies are also needed because we cannot rule out all alternative explanations of our findings. In SI Appendix, we present additional analyses that give us confidence that our results are not driven by Hawthorne effects, partisan “learning” pro- cesses, variation in the ideological extremity of messages by party, or demographic differences in social media use by age. At the same time, we are unable to rule out other alternative explana- tions discussed inSI Appendix. For example, it is possible that our findings resulted from increased exposure to information about politics, and not exposure to opposing messages per se. Similarly, increases in conservatism among Republicans may have resulted from increased exposure to women or racial and ethnic minori- ties whose messages were retweeted by our liberal bot. Finally, our intervention only exposed respondents to high-profile elites with opposing political ideologies. Although our liberal and con- servative bots randomly selected messages from across the liberal and conservative spectrum, previous studies indicate such elites are significantly more polarized than the general electorate (45). It is thus possible that the backfire effect we identified could be exacerbated by an antielite bias, and future studies are needed to examine the effect of online intergroup contact with nonelites.
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Is Social Media an Organic Reach for Business?

Is Social Media an Organic Reach for Business?

After all, we don‟t know how to fix it without understanding how it get broke. The first thing most people will tell you is that Facebook, Twitter, and LinkedIn is just for making money. Well, offcourse it is a business. As we all know, that every business has to make money somehow. Facebook and every other social media platform wants to show users only the content that is most interesting.

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Harnessing Collective Intelligence for the Learning Communities; a Review of Web 2.0 and Social Computing Technologies

Harnessing Collective Intelligence for the Learning Communities; a Review of Web 2.0 and Social Computing Technologies

Social Computing form parts of Web 2.0 era. It is a combination of both social behavior and computational systems. It became the key concept of business nowadays. In simpler term, it uses social conventions to make people interact with each other across the world using software and technology. For better interaction we make use of blogs, email, instant messaging, social network services, wikis, social bookmarking and other instances. In a broader term, it includes collaborative filtering, online auctions, prediction markets, reputation systems, computational social choice, tagging and verification games [5].
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Social Media and Forecasting:
What is the Predictive Power of Social Media

Social Media and Forecasting: What is the Predictive Power of Social Media

Since the advent of Social Media, the World Wide Web has progressed from a state where users used to passively consume information that is provided to them for example by marketers to a diverse Social Media landscape in which users can constantly and actively share and update information (Xu & Liu, 2014). Kietzmann, Hermkens, McCarthy and Silvestre (2011) imply that “Social Media employ mobile and web-based technologies to create highly interactive platforms via which individuals communicate” (p. 241). Cooke and Buckley (2008) characterize a society that is increasingly willing to share their experiences, opinions and thoughts on the so-called “Social Web” and contrary to the traditional media, users of Social Media can publish their own ideas and information online for everyone to read (Hildreth & Ament, 2011; Hoffman & Fodor, 2010). The emergence of a social media ecosystem and the growing usage of social media platforms such as Facebook, Twitter, YouTube and Instagram, only to name a few of the largest ones, have led to a tremendous amount of user-generated content, covering a large variety of topics. Social Web is another term, next to Social Media, that is used to describe the multifaceted Social Media landscape which essentially consists of forums, discussion boards, podcasts, social networks, blogs, microblogs, online chats, video sharing planforms, and photo sharing sites which are originally created to facilitate a social exchange and interaction between people and organizations (Hildreth & Ament, 2011). The Social Media expansion and the information that is shared by millions of users on Social Media platforms create a massive amount of easily accessible data about individuals, society and online behavior of consumers (Schoen et al, 2013
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Social Media Mining: Major Concerns in Social Media Mining

Social Media Mining: Major Concerns in Social Media Mining

The idea behind sentiment analysis is basically to recognize potential drift in the society as it concerns the attitudes, observations, sentiment and the expectations of stakeholder or the people and to make necessary decisions. It is more important to translate sentiment expressed to useful knowledge by way of mining and analysis. Widespread products are likely to attract thousands of reviews and this may make it difficult for prospective buyers to track usable reviews that may assist in making decision. So proper sentiment analysis in social data is important.
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Media Literacy: An Analysis of Social Media Usage among Millennials

Media Literacy: An Analysis of Social Media Usage among Millennials

Smartphones are a media device and these are more popular among adolescents today. Based on the results of a survey conducted by the Ministry of Communication and Information of the Republic of Indonesia, it shows that adolescents are the age group with the highest internet access. For adolescents, smartphones become a part of their lives. With the support of internet access from certain providers, they can access the required information and communicate in various directions with different destinations; therefore, it gets some of them addicted to smartphones [4]. Almost every adolescent has had a smartphone communication tool. A few of them can have more than one smartphone [5]. All this relates to globalization. Globalization makes the world of technology fastest growing. With the development of technology and all the sophistication that a smartphone has, it makes many adolescents amazing and they want to have it [6].
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Social media and social class

Social media and social class

There are limited empirical studies taking a fully Bourdieu based perspective on digital media use. But there is work that has separately explored the economic, social and cultural differences in the types and levels of digital media use. Recent reports by the Good Things Foundation 1 based on work by Yates et al. (2015a), identified over 13 million UK citizens who were limited or non-users of the internet; with the majority being from lower income households. Socio-economic positions therefore influence access to what Selwyn (2003) calls the 'opportunity structure' of digital technologies. This reaches beyond just access to broader digital literacy, highlighting that there are a range of experiences for those categorised as 'digitally included' (Clayton and MacDonald, 2013). We therefore seek to explore this through examining the use of social media in the context of Bourdieu’s three types of capital.
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USE OF SOCIAL MEDIA FOR SOCIAL RESEARCH: AN OVERVIEW

USE OF SOCIAL MEDIA FOR SOCIAL RESEARCH: AN OVERVIEW

Aloia & Naughton (2016) in their research study looked at how social media can be an effective resource disseminating and finding information on grey literature. Persson & Svenningsson (2016) investigate the level of awareness of the professional use of social media among Linkoping University, Sweden researchers and found that use of social media was not significant; however, a small number saw potential. Sriram (2016) through his case study of KN Raj Library of Centre for Development Studies, Thiruvananthapuram explained how social media tools can be effectively put to use in libraries for marketing its resources and services. Gupta (2015)
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Social media as a popular mode for social communication: A review

Social media as a popular mode for social communication: A review

marking produces debilitation of the proposed importance of advertisement, so as to serve the significance of particular gathering, in present scenario, the brand group. An IBC can modify or control the genuine importance of a promotion by way it shows or uses an advertisement for marking. Ordinarily IBCs change the importance of an advertisement by changing the way it is displayed on the group discussion. An IBC can adjust a promotion to conform to the subject of its group, in such a manner that the advertisements genuine significance gets lost. A person's online personality coupled with the social group's traditions influences the route in which individuals view promotions exhibited via social networking media. Group traditions can be influenced by clients' social foundations as well. Pookulangara and Koesler (2011) utilized the Technology Acceptance Model3 (TAM3) to take a glimpse at the effect of culture on social networking media. TAM3 highlights the part and techniques associated with ‘saw helpfulness’ and ‘saw simplicity of innovation’. TAM3 proposes that the variables that decide ‘saw value’ won't impact ‘saw convenience’ and the components that impact ‘saw usability’ won't impact ‘saw handiness’ (Pookulangara and Koesler, 2011). The analysts utilized TAM3 to see whether a person's social foundation influences ‘saw ease’ and ‘saw convenience’ keeping in mind the end goal to observe clients' behavioral goal towards online networking. All the more, the analysts particularly utilized TAM3 to decide whether a person's social foundation impacts the way they decipher a message, occasion, or thought introduced to them through an informal communication site. This was done through a theoretical structure in which the analysts made an exploration utilizing TAM3.
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