Scientists' use of social media: The case of researchers at the University of the Philippines Los Banos
First Monday

Scientists' use of social media: The case of researchers at the University of the Philippines Los Banos by Florante Cruz and Serlie B. Jamias



Abstract
Using proportional random sampling, 86 researchers working at the University of the Philippines Los Baños (UPLB) were chosen as respondents of a survey study that aimed to determine scientists’ perceptions and use of social media for research. The study also investigated the influence of several factors — age, awareness, Internet connectivity, research style, and technology adoption behavior — on the scientists’ use of social media in research and research–related activities. Results showed that age, connectivity, research style, and technology adoption behavior did not influence the use of social media by UPLB scientists in research. The study also found age to be correlated to factors such as connectivity, research style and awareness of social media. On the other hand, the researcher’s connectivity and broad discipline were found to be correlated to his or her awareness of social media tools. In conclusion, awareness of social media tools roughly translated into actual use of social media in research. In spite of this, a considerable gap exists between awareness and actual use of social media in research by UPLB researchers. In terms of policy, it is suggested that the university administration take a hard look at the benefits and tradeoffs of integrating the use of social media in various aspects of instruction, research, and extension. A social media use policy should be carefully crafted and appended to the University’s existing acceptable use policy for Internet resources.

Contents

Introduction
Review of related literature
Theoretical and conceptual framework
Hypotheses
Methodology
Results and discussion
Conclusions and recommendations

 


 

Introduction

Background

More than 30 years ago, social scientists William Garvey and Belver Griffith introduced a model that argues that communication — formal and informal — is the “essence” of science. Since the development of this model, emerging information technologies have dramatically altered and enhanced scientists’ options for communication (Hurd, 2000).

Among the technologies that gave shape to what science communication is today are the so–called “social communication technologies” — elaborated by Koo, et al. in 2011 as any technology used for social purpose, which includes social hardware (e.g., telephone), social software (e.g., instant messenger, video conferencing, e–mail), and social media (e.g., blogs, Twitter, Facebook, YouTube, etc.).

The role of social media in communication has become so globally popular and important that, as of 2011, 84 percent of Fortune 100 firms are using at least one of the four most popular social media platforms (Barnes and Lescault, 2011). In the area of development, Chou, et al. in 2009 cited social scientists’ observations that social media have increased individuals’ connectivity and enabled users’ direct participation and were thus believed to have direct implications for health communication programs that can impact on population health.

On the education front, a 2011 study of the Center for Marketing Research of the University of Massachusetts–Dartmouth showed that 100 percent of U.S. colleges and universities are now using some form of social media.

The importance and impact of social media are not only felt within the academe but also in the realm of science and research. In fact, Vasileiadou and Vliegenthart underscored in 2009 that the increasing use of the Internet in research has brought forth several studies on whether the Internet facilitates research work and improves productivity.

Although the Internet is generally seen as a tool that improves research by providing access to resources and facilitating sharing of files, data, and ideas (Walsh, et al., 2000), there is a huge potential for using social media for networking. Romain Murenzi, executive director of the Third World Academy of Sciences, shared that social media platforms can “help scientists get together and work on shared areas of interest ... and also dramatically reduce the need for developing–country scientists to travel to meetings and conferences” (Nordling, 2011).

Social media is now considered important for scientists in their daily communication activities. Rowan recently reported in May 2011 that an increasing number of scientists are starting to use these tools to talk about science: writing blogs about their work, papers they have read and activities in their laboratories, or using Twitter to collect and share stories and resources with like–minded colleagues.

And as such, “social media has become a serious academic tool for many scholars, who use them for collaborative writing, conferencing, sharing images, and other research–related activities” (Howard, 2011).

Social media therefore has a special capability and place in improving research culture and productivity within and among research–based institutions with substantial Internet resources.

Although awareness of social media among members of the research community is high, there is a large gap between awareness and actual use for majority of these tools (Cann, et al., 2011). Vasileiadou and Vliegenthart’s findings in 2009 suggest that the positive impact of Internet use on research productivity is limited and may only be relevant only when collaborative endeavors suffer from coordination problems, inferring that scientists may have preferences when it comes to social media use. These preferences may be attributed to factors such as demographics, attitude, behavior, skills or other social aspects of the scientist and, as reported by McAfee, Inc. in its 2010 global study, the attendant risks of social media use on concerns such as organizational productivity, legal issues, reputation, and security.

The U.K.–based Research Information Network in 2010 also cited several critiques of social media use, to cite a few: misuse of scientific data; exposure and attack on the scientific opinions and ideas which have not been subject to peer review; information overload; and, loss of authoritative perspectives.

In the Philippines, some studies, such as those by Liggayu (2010) and Chua and Peralta (2011), have earlier investigated the relationships and value of social media in education and learning. Communication–related factors that affect the acceptance of social networking sites by UPLB students have also been studied by Collado in 2008.

However, the gaps abovementioned remain unknown in scientific communities, such as among scientists of UPLB.

Statement of the problem

Understanding the UPLB science community enables one to know what underlying considerations are important in the adoption of social media for research purposes in the university. Thus, the problem is stated as: “How do UPLB scientists perceive social media for research? Do they use social media in their research work? How and for what?”

Objectives of this study

This study aims to determine the use of social media by scientists and researchers at UPLB for research. Specifically, these objectives are:

  1. Find out what social media scientists are aware of and knowledgeable about;
  2. Determine how scientists perceive social media in terms of its usefulness in the research cycle, perceived benefits, and barriers to its use in research;
  3. Determine the social media use of scientists; and,
  4. Determine how the scientists’ socio–demographic profile and perceptions are related to social media use.

Significance

Although there have been studies on perceptions, preferences, and other social aspects of the use of social media by scientists and members of the academe, some of these have large sampling sizes and encompass large geographical areas, findings from which cannot provide generalizations on the behavior of a scientist who is easily affected by his or her specific environment.

For instance, the use by a scientist or researcher of social media for interpersonal communication can be negatively affected by the lack of physical infrastructure or his or her level of skills or cultural background. The study is therefore important to provide new knowledge on social media and the scientist in the local context.

On a different note, UPLB, as a public service and research university, is now expected to further improve its system in communicating with and engaging the public. The results of the study will be invaluable as a policy input specially that, as of date, UPLB has to fully consider the applications of social media for public relations and academic and research productivity.

 

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Review of related literature

Scientists, researchers, and members of the academe have networks, in one form or another. Foremost of the scientist’s network is the ‘invisible college,’ recently given a new definition by Zuccala in 2006 as a “set of interacting scholars or scientists who share similar research interests concerning a subject specialty, who often produce publications relevant to this subject and who communicate both formally and informally with one another to work towards important goals in the subject, even though they may belong to geographically distant research affiliates.”

In 2009, Lind presented that in networks, people and organizations share knowledge and resources around a solution to a specific problem in their environment. It is by sharing that scientists become in need of constant communication.

The Internet and research

Information technologies, particularly the personal computer and the World Wide Web, have changed the ways scientists network and communicate.

Studies made more than 20 years ago, such as that of Freeman (1984), have already suggested that the computer can take the place of face–to–face interaction among scientists, providing a sort of social structure in which a scientific specialty can grow.

Eisend (2002) reported that the Internet substitutes for written communication media and complements forms of spoken communication in the field of research. His study also acknowledged that the use of the Internet has become institutionalized in the field of research as a medium of interpersonal communication.

Smith, in her study on crystallographers of South Africa in 2007, clearly showed that the significant increase in the use of electronic modes and systems, while not affecting the inherent structure of the communication process, has a positive influence on ease of communication and collaboration. In the same year, Sooryamoorthy and Shrum (2007) found, through a survey of 275 scientists in South Africa’s KwaZulu–Natal province, that Internet use, as measured by time spent on e–mail, is positively associated with collaboration. Vasileiadou and Vliegenthart in 2009 also cited several studies that showed a general positive relationship between Internet use and research productivity.

Social media for communication

Social media is a social communication technology (Koo, et al., 2011) meanwhile defined social media as a group of Internet–based applications that build on the ideological and technological foundations of Web 2.0 (where sites facilitate interaction and collaboration among users in a social media dialogue), and that allow the creation and exchange of “user–generated content.”

It can also be described as online technologies and practices that people use to share opinions, insights, experiences, and perspectives. Social media can take many different forms, including text, images, audio, and video. These sites typically use technologies such as blogs, message boards, podcasts, wikis, and vlogs or video blogs to allow users to interact (Cann, et al., 2011).

As a communication tool, social media is heavily considered for fields such as organizational public relations, health and crisis communication, social mobilization, and many more.

For companies, social media is important because aside from it enabling them to talk to customers, it also enables customers to talk directly to one another (Mangold and Faulds, 2009). In health care, social sites such as YouTube, Facebook, MySpace, Twitter, and Second Life are rapidly emerging as popular sources of health information, especially for teens and young adults. Social media marketing carries the advantages of low cost, rapid transmission through a wide community, and user interaction (Vance, et al., 2009).

In the area of education, Danciu and Grosseck found in 2011 that more and more colleges and universities from all over the world are widening their curriculum landscape beyond technology by integrating different forms of social media, such as (micro) blogging, collaborative content, social networking, multimedia sharing, casting (pod–, screen–, etc.), social bookmarking/tagging, and other online social artifacts.

The nature of the use of social media specifically for communication by scientists, for varied reasons such as networking, collaboration, public engagement and others, also have garnered numerous scientific inquiries. Among the recently published is that of Bukvova (2011) who studied scientists’ online profiles on institutional and private Web pages, social networking services, blogs, and microblogs because online self–presentation of scientists can serve to improve the awareness of and communication within the scientific community. Kjellberg (2010) showed that the scientists’ blogging is motivated by the possibility to share knowledge, that the blog aids creativity, and that it provides a feeling of being connected in their work as researchers.

Although scholars acknowledge the great potential of social media for the research community, these tools are not without barriers. Eva Amsen, former prolific science blogger at nature.com and now manager of a community Web site for biologists, reported in 2009 that the image of Web 2.0, lack of familiarity with new tools, lack of time, perceived lack of personal/career benefits, and fear of being scooped or losing one’s job are among the reasons scientists do not like it. Cha (2010), on the other hand, found that interpersonal utility, perceived ease of use, privacy concerns, and age determine the use (and frequency) of the tools that deliver social media, social networks in particular. Muñoz and Towner (2011) also identified some hurdles in the use of social networking sites such as Facebook in education: erosion of professional boundaries, privacy and safety, computer security issues, adoption issues such as lack of time, interest, or Internet access.

Social media and communication in the research cycle

In its 2010 study, the U.K.–based Research Information Network discussed the still limited understanding of factors that influence the adoption of Web 2.0 and how it is being used by researchers. The implications for scientists and their practices in the research environment, as well as for policies revolving around funding and organizations are yet to be documented. To study the adoption and use of social media and its tools, one should look at the activities a scientist or researcher does in the course of scientific communication.

To understand how and why scholars do what they do to advance their fields as well as their careers, Harley, et al. (2008) analyzed the values and behavior of faculty throughout the scholarly communication lifecycle, which includes sharing, collaborating, publishing, and engaging with the public.

So, in order for us to better know what “scholarly communication” encompasses, we refer to Procter, et al.’s (2010) definition of scholarly communication, as doing the following tasks: (1) conducting research, developing ideas and informal communications; (2) preparing, shaping, and communicating what will become formal research outputs; (3) dissemination of formal products; (4) managing personal careers and research teams and research programs; and, (4) communicating scholarly ideas to broader communities.

In late 2010, CIBER and its partners released the results of a survey that determined the use of social media in the research workflow. It included these activities of researchers: (1) identifying research opportunities; (2) finding collaborators; (3) securing funding support; (4) reviewing literature; (5) collecting research data; (6) analyzing research data; (7) disseminating findings; and, (8) managing the research process.

Local scholarship on scientists and social media

Little is known about the scientists’ thoughts on technological developments in information and communication technology, such as social media and Web 2.0, in relation to their work.

Although Ponte and Simon (2011) recently explored the habits of researchers and their opinions regarding the many innovations happening in the field of scientific publishing and scholarly communication; and, showed that scientists have a strong positive attitude towards Web 2.0; his team still professed that there is a dearth of scholarship in these areas.

This is the same case in the Philippines where specific literature on the use or consumption of scientists and researchers of social media for research is probably, as of this writing, greatly lacking. Nonetheless, a handful of past local research on scientists can provide useful, related information.

Earliest among these local studies were by Taihitu (1997), which revealed that, at that time, 50 percent of scientists at UPLB prefer the Internet as an information source, and majority of the respondents from different fields of specializations find sufficient information in the Internet related to their fields. Next in line was that of Garcia (1999), which showed that scientists in the Los Baños science community perceive the Internet as an important and adequate channel of science and technological information.

In 2001, Adversario found that UPLB scientists consider themselves as communication channels geared towards the public, other scientists, and research–funding agencies. Interpersonal communication is very much used in communicating with the public and other scientists. Also, in 2001, Ibarrola found that 36 percent of her faculty respondents used the Internet because of the availability of updated information online. Those who do not use (20 percent) the Internet cited reasons such as “too time consuming,” “no immediate need,” and “do not know how to,” and “they already have an assistant to do the task.”

Maglalang (2002) showed that Internet use is significantly correlated to scientific productivity in terms of “kind of information sought,” inferring that specific Internet sites are important to scientists’ productive work.

Collado (2008) studied the socio–demographic characteristics, communication participation, source accessibility, frequency of use, perceived attributes of social networking sites, and psycho–cultural factors of UPLB students in relation to their acceptance of social network sites.

An exploration on the use of social networks in agriculture had been made by the Open Academy for Philippine Agriculture in 2009, starting with the development of a Ning–based social Web site to connect rice stakeholders such as scientists, farmers, and extension workers; it gives us a peek at reasons people from the academic and scientific arena seek ways to communicate with their clients.

Lastly, Liggayu (2010) revealed that social networking sites are potential tools for learning media, specially if faculty and teachers know how to properly use them for academic purposes.

 

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Theoretical and conceptual framework

Communication theories for the Internet environment

Uses and gratifications theory. Questioning what really encourages people to cooperate in a “solution sharing network,” Lind (2009) suggested that the uses–and–gratification (U&G) theory may explain how people in a particular network use different media to fulfill their needs.

The theory can be considered a paradigm within media and communication research to determine motivation by studying the use of mass media. To elaborate, motivations for use of mass media are determined by needs exhibited by people: cognitive, affective, personal integrative, tension release (Katz, et al., 1973; Severin and Tankard, 1997). As another example, television is associated with entertainment, whereas the Internet is more related to information seeking (Straubhaar, et al., 2012). Other scholarly studies also point that the theory may be used to clarify how people use electronic communication environments to fulfill their needs.

Kuehn, as cited by Ruggiero (2000), emphasized that the interactive capacity of computer–mediated communication needs a newer “needs” typology: convenience, diversion, relationship development, and intellectual appeal.

Stafford, et al. described in 2004 three key dimensions related to consumer use of the Internet, including process and content gratifications as previously found in studies of television, as well as an entirely new social gratification that is unique to Internet use.

Ko, et al., after investigating a marketing Web site in 2005, identified four dimensions of Internet uses and gratifications: information, convenience, entertainment, and social–interaction motivations. They found that consumers who have high information motivations are more likely to engage in human–message interaction on a Web site, whereas social interaction motivations are more strongly related to human–human interaction.

In spite of the continuing scholarship and theory–building on U&G, the approach has been regarded as better suited to studying Internet use because users are more actively engaged communication participants in the Internet environment as compared with degrees of engagement in other traditional media (Hou, 2011).

Technology acceptance model. The technology acceptance model (TAM) was proposed by Davis in 1985 as an instrument to predict the likelihood of a new technology being adopted within a group or an organization (Legris, et al., 2003).

For example, Shih (2004) has shown, using TAM, that the relevance of information needs strongly determines perceived usefulness, perceived ease of use, and user attitudes toward Internet use for information seeking, as well as strongly influencing individual performance during the information use stage.

The TAM, however, has its limitations. Although it has been widely used to study user acceptance of new technologies, it does not incorporate social structure and influence as a significant factor (Hossain and de Silva, 2009). Turner, et al. (2010), in their review of literature on TAM, gathered evidence that behavioral intent to use is likely to be correlated with actual usage. TAM’s variables perceived ease of use and perceived usefulness are less likely to be correlated with actual usage.

Nonetheless, TAM is still a useful model which, as Un Jan and Contreras has shown in 2011, can be used in drawing up policy recommendations for the use of information technology in organizations such as universities.

Conceptual framework

This study is an exploratory study on the use of social media by scientists for research. Use, as shown by Figure 1 below, is determined by two independent variables, socio-demographic profile and perception of social media.

 

Conceptual framework of this study
 
Figure 1: Conceptual framework of this study.

 

 

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Hypotheses

Most of the findings by past studies on scientists’ use of social media cannot be generalized for all researchers. It is also therefore the intention of this study to determine whether socio–demographic characteristics and perceptions of UPLB scientists and researchers influence their use of social media for research purposes. The following hypotheses will be tested:

H1. Age is correlated to the UPLB scientist’s use of social media for research.
H2. Internet connectivity is correlated to use of social media for research.
H3. Awareness of social media tools is correlated to the UPLB scientist’s use of social media for research.
H4. Style of research is correlated to the UPLB scientist’s use of social media for research.
H5. Technology adoption behavior is correlated to the UPLB scientist’s use of social media for research.

 

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Methodology

Respondents and sampling

From an eligible population of 847 faculty and research, extension, and professional staff (REPS), 86 respondents were proportionately and randomly selected based on their broad disciplines. Derivation of the sample size at 95 percent confidence level, 10 percent sampling error at 50/50 split was based on Dillman (2007).

Data were collected through mix–mode collection, i.e., self–administered survey questionnaire and online survey made through Google Docs embedded within the Web site of UPLB’s Office of the Vice–Chancellor for Research and Extension. The survey was kept short to prevent the perception of “time–off–task” that may jeopardize the results of the survey.

Data gathering and analysis

The survey instrument, which used Likert–type scales and input forms, was developed and given directly to the identified respondents. Most of the variables that was measured were adopted from the earlier study of CIBER. Respondents were given the choice to either use the paper–based or online survey. The respondents were given two weeks to complete the survey.

Descriptive statistics such as percentages and means were derived from the gathered data using Statistical Package for the Social Sciences (SPSS) software. To determine relationships between the independent and dependent variables, Spearman rank correlation was used.

 

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Results and discussion

From data given by the 86 respondents, percentages were computed to describe the socio–demographic profile of researchers at UPLB.

Faculty and REPS faculty comprised the majority (72.1 percent) of the research manpower, while full–time REPS made up a little more than a fourth (27.9 percent). According to age, the respondents were distributed to 35 and below (23.1 percent), 36 to 45 (22.1 percent), 46 to 55 (32.6 percent), and 56 and above (22.1 percent).

In terms of educational attainment, those with masteral degrees comprised almost half (48.8 percent) of the population, whereas 39.5 percent held Ph.D. degrees. BS/DVM and postdoctorate degree holders have similar percentages (5.8 percent). Most of the respondents received their degrees from universities in the country (61.6 percent) while 25 percent garnered their degrees both locally and from abroad.

UPLB researchers (n=85) connected to the Internet at the following locations: (a) at the office (7.1 percent); (b) both at home and the office (49.4 percent); (c) and at home, at the office, and even when going around using mobile devices (43.5 percent).

The proportion of researchers based on broad disciplines is as follows: agriculture and forestry science, 34.9 percent; business and management, 9.3 percent; engineering and technology, 11.6 percent; mathematical sciences, 5.8 percent; natural and physical sciences, 14 percent; social sciences, 22.1 percent; and others, 2.3 percent.

In terms of research style, 23.3 percent of the respondents indicated that they work with collaborators from other universities/organizations. Another 23.3 percent stated that they work with collaborators across the university. More researchers (46.5 percent) work with colleagues in their respective departments or college. A small percent (7 percent) work on their own.

In terms of Roger’s technology adoption behavior, 22.1 percent of the respondents considered themselves as innovators. A big portion (40.7 percent) stated that they are early adopters, while the early majority comprised 25.6 percent. The remaining respondents (11.6 percent) considered themselves as technology laggards. None answered that they are part of the late majority.

Awareness of social media tools

Respondents were more aware of or familiar with social networking as a social media tool, having a mean score of 4.11 from a possible 5.0. Image and video sharing (3.77) and conferencing (3.66) are the two next familiar social media tools. Figure 2 shows the mean scores on awareness of the other social media tools.

 

Mean scores for awareness of various types of social media tools
 
Figure 2: Mean scores for awareness of various types of social media tools on a five–point scale where 1=unfamiliar and 5=extremely familiar.

 

Perceived usefulness of social media tools in the research cycle

Respondents were asked how useful the identified social media tools are as applied in various stages of the research cycle (Figure 3). Compared with the other social media tools, Wikis and Google Docs were regarded more useful in identifying research opportunities, whereas networking tools such as Facebook, Google+, and LinkedIn were better for finding research collaborators. In reviewing literature, respondents found Wikis, Google Docs, Academia, and Mendeley most useful. The data also suggest that social media tools have little use in securing funding support, gathering and analyzing data, and managing the research process. However, respondents generally found the various social media tools as useful for communicating research results.

 

Identifying research opportunities
Identifying research opportunities.
Finding research collaborators
Finding research collaborators.
Securing funding support
Securing funding support.
In reviewing literature
In reviewing literature.
Gathering and analyzing data
Gathering and analyzing data.
Managing the research process
Managing the research process.
Disseminating and communicating research results
Disseminating and communicating research results.
 
Figure 3: Mean scores for perceived usefulness of various social media tools in the research cycle on a five-point scale where 1=not at all useful and 5=extremely useful.

 

Perceived usefulness of social media tools in the research cycle, by discipline group

Figure 4 shows how UPLB’s different scientific discipline groups view the usefulness of various social media tools in the research cycle. The graph areas indicate the respondents’ view that social networking, scientific article sharing, and collaborative authoring tools were the ones most useful in the research process, while micro–blogging and conferencing were least useful.

 

Social networking
Social networking
Scientific article sharing
Scientific article sharing
Presentation sharing
Presentation sharing
Blogging
Blogging
Collaborative authoring
Collaborative authoring
Micro-blogging
Micro–blogging
Conferencing
Conferencing
Video and image sharing
Video and image sharing
Index
 
Figure 4: Mean scores for perceived usefulness of various social media tools in the research cycle, by broad discipline group, on a five–point scale where 1=not at all useful and 5=extremely useful.

 

Value as a source of scientific information

Compared with traditional forms, social media and networks ranked lowest (3.79) in terms of value as a source of scientific information (Figure 5). Expectedly, UPLB researchers found academic journals (4.92), books/monographs (4.70), and conference proceedings (4.62) as very valuable sources of scientific information.

 

Mean scores for awareness of various types of social media tools
 
Figure 5: Mean scores for awareness of various types of social media tools on a five–point scale where 1=unfamiliar and 5=extremely familiar.

 

Frequency of looking for and disseminating research information

UPLB researchers were asked how and how often do they look for and disseminate research information (Figure 6). The calculations made infer that UPLB scientists searched the open Web and subscription–based content such as journals when in need of scientific information. On the other hand, publishing articles in journals and presenting papers in conferences were the main venues for research dissemination of UPLB scientists.

 

frequency of sourcingfrequency of disseminating research information
 
Figure 6: Mean scores for frequency of (A) sourcing and (B) disseminating research information a five–point scale where 1=always and 5=never.

 

Importance of social media in reaching target audiences

Consistent with the largely held view that social media is able to reach a wide range of audiences, respondents generally answered that social media is very important in reaching not only as many people as possible (4.31) but also other partners in research and development (Figure 7).

 

Mean scores for perceived importance of social media tools in sharing research results to various clientele
 
Figure 7: Mean scores for perceived importance of social media tools in sharing research results to various clientele on a five–point scale where 1=not at all important and 5=extremely important.

 

Researchers’ frequency and use of social media for research

Asked what social media tools have UPLB researchers actually used in their research activities and how often, respondents indicated (Figure 8) that they frequently used collaborative authoring (2.69) tools such as Google Docs and social networking tools (2.73), presumably Facebook.

 

Mean scores of researchers' frequency of social media use for research
 
Figure 8: Mean scores of researchers’ frequency of social media use for research on a five–point scale where 1=always and 5=never.

 

A large portion of researcher respondents indicated that they have actually used collaborative authoring tools (88.37 percent) and social networking (81.40 percent) in research (Figure 9). Almost a fourth (23.53 percent) answered that they have used all of the social media tools.

 

frequency of sourcingfrequency of disseminating research information
 
Figure 9: Mean scores for frequency of (A) sourcing and (B) disseminating research information a five–point scale where 1=always and 5=never.

 

Researchers using social media, by age and technology adoption behavior

The data collected were also analyzed to determine the percentages of researchers (who actually have used the specified social media tool) in terms of age (Figure 10) and technology adoption behavior (Figure 11). Most notable from the graphs are the findings that (a) most users were aged 46 to 55 and (b) most users identified themselves as early adopters.

 

Percentage of UPLB researchers, by age group, within each category tool that has been actually used
 
Figure 10: Percentage of UPLB researchers, by age group, within each category tool that has been actually used.

 

 

Percentage of UPLB researchers, by Roger's innovation type, within each category tool that has been actually used
 
Figure 11: Percentage of UPLB researchers, by Roger’s innovation type, within each category tool that has been actually used.

 

Benefits of social media in research

Generally, researchers agreed that using social media is beneficial in terms of being efficient and productive in research work (Figure 12). Respondents, however, indicated that they did not equate social media use that much to becoming more popular or reputable (1.74) in online scientific communities.

 

Mean scores of researchers' perception of the benefits of social media use in research
 
Figure 12: Mean scores of researchers’ perception of the benefits of social media use in research on a scale where 1=agree and 3=disagree.

 

Drivers of and barriers to using social media in research

Respondents answered that technology (3.71) and personal initiative (3.67) were two key drivers that influence the use of social media in research (Figure 13). Interestingly, the mean score for University management (2.83) showed that it does not have any bearing on the adoption of social media use for research purposes in the University.

 

Mean scores of researchers' perception of the drivers of social media use in research
 
Figure 13: Mean scores of researchers’ perception of the drivers of social media use in research on a scale where 1=not at all influential and 3=extremely influential.

 

With regard to the influence of identified barriers to using social media in research (Figure 14), slow Internet speed (4.16) topped the list as the most influential barrier. The next two influential barriers were ‘unsure of rights and copyright’ (3.52) and ‘lack of time’ (3.29).

 

Mean scores of researchers' perception of the barriers of social media use in research
 
Figure 14:Mean scores of researchers’ perception of the barriers of social media use in research, on a scale where 1=not at all influential and 3=extremely influential.

 

Socio–demographic factors related to the use of social media in research

A Spearman’s rank order correlation was run to determine the relationship between the various socio–demographic variables of the 86 respondents and their awareness and use of social media in research.

Among the major findings of the correlations (Table 1), in the case of researchers at UPLB, were the following:

  1. There was no significant correlation between (a) age and social media use; (b) connectivity and social media use; (c) style of research and social media use; and, (d) technology adoption behavior and social media use.
  2. Age was negatively correlated to the following: connectivity (r=-.237, n=86, p=.029) , research style (r=-.213, n=86, p=.049), and awareness (r=-.487, n=86, p=.000).
  3. Connectivity (r=.253, n=85, p=.020) and broad discipline (r=.257, n=86, p=.017), were correlated to awareness.
  4. There was moderate correlation between awareness of social media tools and use of social media in research (r=.-561, n=86, p=.000).

The study’s hypotheses that there are correlations between a) age and social media use; (b) connectivity and social media use; (c) style of research and social media use; and, (d) technology adoption behavior and social media use were thus all rejected.

 

Correlation table of different variables that related to the awareness and/or use of social media in research by UPLB scientists
 
Table 1: Correlation table of different variables that related to the awareness and/or use of social media in research by UPLB scientists.

 

The correlation between awareness of social media tools and use of social media tools in research is presented as a scatter plot in Figure 15. Moderate correlation between the variables indicated that, as awareness increases, the use of social media tools also increases.

 

Scatter plot of the correlation between awareness and use of social media tools by UPLB researchers
 
Figure 15: Scatter plot of the correlation between awareness and use of social media tools by UPLB researchers, where in the Use axis 1=always and 5 =never.

 

 

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Conclusions and recommendations

In general, this study determined the socio–demographic profile of researchers from UPLB and their use of social media in research. This study also investigated the influence of several factors — age, awareness, Internet connectivity, research style, and technology adoption behavior — on the scientists’ use of social media in research and research–related activities. Results indicated that age, connectivity, research style and technology adoption behavior do not influence the use of social media by UPLB scientists in research.

Rowlands, et al. (2011) also reported that age is a poor indicator of social media use but stated, however, that Rogers’ model of technology adoption is a good predictor of social media takeup. This study also found age to be correlated to factors such as connectivity, research style, and awareness of social media use. On the other hand, the researcher’s connectivity and broad discipline were found to be correlated to his or her awareness of social media tools.

Awareness of social media tools roughly translated into actual use of social media in research. In spite of this, there seems to exist a considerable gap between awareness and actual use of social media in research by UPLB researchers.

Considering that UPLB researchers generally have a high regard for the benefits social media can provide in research (Figure 12) — an encouraging factor for social media to be easily adopted by researchers — factors such as the influence of drivers and barriers may have had effects on the actual use of social media in research.

In the case of UPLB researchers, University management has little bearing (Figure 13) on the use of social media, suggesting that an active administration role in promoting social media use for research productivity is lacking. Meanwhile, slow Internet speed (Figure 14) definitely affects the accessibility of social media tools by the researchers.

In terms of policy, it is suggested that the UPLB administration take a hard look on the benefits and tradeoffs of integrating the use of social media in various aspects of instruction, research, and extension. A social media use policy should be carefully crafted and appended to the university's existing acceptable use policy for Internet resources.

As part of continuing scholarship on this area, it is recommended that future inquiries on social media use by researchers involve a larger sample of respondents to ensure better generalizations. Also, more independent variables can be added to the research model in order to identify or verify other important factors that affect social media use in research. Another study on a contrast group (i.e., non–users of social media), done separately or in comparison with users is also a worthwhile academic inquiry. The study can also be further improved in order to accurately determine the impact of research style and technology adoption behavior on social media use in research. Both variables, according to the 2010 report by CIBER, University College London and Emerald Group, are powerful predictors of social media takeup.

Lastly, similar studies can be done in terms of use of social media in other university functions such as teaching and administration. The study can also be replicated to organizations of scientists such as professional societies in order to get an in–depth look at social media use in specific scientific disciplines. End of article

 

About the authors

Florante A. Cruz is University Researcher I at the University of the Philippines Los Baños.

Serlie B. Jamias is Associate Professor, College of Development Communication and Director, Office of Public Relations, at the University of the Philippines Los Baños.

 

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Editorial history

Received 14 November 2012; accepted 5 February 2013.


Copyright © 2013, First Monday.
Copyright © 2013, Florante Cruz and Serlie B. Jamias.

Scientists’ use of social media: The case of researchers at the University of the Philippines Los Baños
by Florante Cruz and Serlie B. Jamias.
First Monday, Volume 18, Number 4 - 1 April 2013
http://firstmonday.org/ojs/index.php/fm/article/view/4296/3650
doi:10.5210/fm.v18i4.4296





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