NEW PERSPECTIVES FOR SEARCH IN SOCIAL NETWORKS

A Challenge for Inclusion

Júlio Cesar dos Reis

Institute of Computing (UNICAMP) and CTI Renato Archer

Rodovia Dom Pedro I, km 143,6, 13069-901, Campinas, São Paulo, Brazil

Rodrigo Bonacin

CTI Renato Archer and Faculty of Campo Limpo Paulista (FACCAMP)

Rua Guatemala, nº 167, 13231-230, Campo Limpo Paulista, São Paulo, Brazil

M. Cecilia C. Baranauskas

Institute of Computing at University of Campinas (UNICAMP)

Caixa Postal 6176, 13083 970, Campinas, São Paulo, Brazil

Keywords: Semantic Web, Semantic Search, Inclusive Social Network Services, Organisational Semiotics.

Abstract: The world is populated with many scenarios characterized by a diversity of cultures and social problems.

Thus it is necessary to investigate computational solutions that respect this diversity. The use of search

engines is one of the main mechanisms to provide the access to information generated in the Social Network

Services (SNS). These mechanisms are currently built through lexical-syntactical processing resulting in

barriers for many users to access correct and valuable information in the Web. Novel search mechanisms

could effectively help people to recover and use information through Inclusive Social Networks Services

(ISN), promoting the universal access to information. This paper shows results of search activities in an ISN

that point out how to improve search engines considering aspects related to social and digital inclusion.

Inspired in these results, we outline an approach based on Organisational Semiotics to build Web ontology,

which is used by an inclusive search engine drawn up in this paper. Actually, this proposal combines

different strategies to provide better search results for all.

1 INTRODUCTION

Web systems and portals are available to a vast

number of people with socio-cultural differences.

Within a Social Network, people communicate and

behave according to commitments, linguistic

constraints, culture and other social aspects. Social

Network Services (SNS) of nowadays could be more

appropriate to the context of people´s life,

considering their differences, in order to promote

social and digital inclusion.

This scenario becomes even more challenging

and important in contexts such as Brazil, where there

are several social problems and a huge cultural

diversity. In this perspective, one of the fundamental

points is to provide barriers free access to

information to every citizen. This could help to bring

great social benefits and contribute to a profound

social transformation. Thus, it is extremely

important that all people have the opportunity to

retrieve, access and use information provided in the

digital media in a smooth way.

The SNS represents an opportunity to

interaction, access to information and knowledge

through the Web. These systems primarily allow

individuals to share their interests and activities,

constituting communities. The e-Cidadania project

(Baranauskas, 2007) aims at transforming a SNS

into an engine for digital inclusion and citizenship.

The networks with such characteristics can be

defined as "Inclusive Social Network Services”

(ISN) (see Neris et al., 2009). The use of search

Reis J., Bonacin R. and C. Baranauskas M. (2010).

NEW PERSPECTIVES FOR SEARCH IN SOCIAL NETWORKS - A Challenge for Inclusion.

In Proceedings of the 12th International Conference on Enterprise Information Systems - Human-Computer Interaction, pages 53-62

DOI: 10.5220/0002897000530062

 SciTePress

engines is one of the primary ways to find and to

make access to information generated in these

systems. However, search mechanisms are currently

built based on comparisons of keywords and lexical-

syntactical information processing (syntax search).

These mechanisms are not sufficient and adequate to

effectively make sense to individuals in an inclusive

scenario within social networks.

Based on empirical results, which will be

discussed in this paper, we have observed that

people organized into virtual communities bring to

this space their own vocabularies and meanings, and

also develop their own local vocabularies through

interaction and communication using technology.

The results pointed out the need for novel search

mechanisms considering the diversity of users’

competencies and inclusion aspects.

A more appropriate inclusive search solution to

an ISN should reflect the semantics used by

participants of the social network. In few words, a

search engine should take into account the local

meanings created, shared and used by people

organized into a community. In this paper we argue

that the quality and response accuracy of a search

mechanism are intrinsically associated to the

proximity of the semantics shared by people. Thus,

it is necessary to identify the meanings used in the

network and to represent its semantic aspects. This

could actually contribute to make the information

accessible to everyone, including people with low

educational levels that have difficulty to access

online information due to their simple vocabulary or

their deficiency in writing. Usually, these people use

an informal (colloquial) or local vocabulary in the

search. With the proposed solution they could find

the correct information in an easier and more precise

way, and learn from it.

In this paper we show results of search activities

within an ISN, conducted in the context of the e-

Cidadania project. The goal of these activities was to

observe a set of search scenarios with potential users

of an ISN, and to understand how these users make

sense of a search mechanism. Based on the results,

we present a proposal of developing a more

appropriate search mechanism for an ISN with

foundations in Organisacional Semiotics (OS)

(Stamper 2001; Liu 2000). In our approach the goal

is to expand and to improve the search technologies

and techniques of the Semantic Web field. Besides,

the representational structure (semantic model) used

by the search mechanism is based on data from the

interaction and communication of users in the social

network system. Thus, the search engine will take

into account the meanings shared and created by

people (including the informal terms) in their

interaction with the system aiming to provide better

results.

The paper is organized as follows: Section 2

presents the concept of ISN and the importance of

search mechanisms for the universal access to

information; Section 3 presents the analysis of the

empirical experiment with ISN users; Section 4

details the proposed approach; Section 5 makes a

discussion about the approach and related works;

and Section 6 concludes presenting further works.

2 UNIVERSAL ACCESS

AND INCLUSIVE SEARCH

According to Boyd & Ellison (2008) since the

beginning of the Social Networking, sites such as

MySpace, Facebook, Orkut and others have attracted

millions of users and many of them have integrated

these sites into their daily practices.

Online Social Networks or "communities of

members" have great relevance in the Web as users

spend much time of navigation on them. According

to Nielsen (2009), social networks are more popular

than e-mail, with 66.8% of global reach. Around the

world it represents the fourth most used resource in

the Internet and 85.2% of penetration are in the

portals and communities of general interest.

Additionally, 85.9% of Internet users use search

engines, which is one of the most common activities.

Despite these great numbers and the success of

Social Network sites among Internet users, in social

contexts like Brazil and other developing countries,

there are yet a lot of people without access to the

Internet and consequently without opportunities to

access information and knowledge. Social indicators

shown by the PNAD (National Survey by Household

Sample) produced by IBGE (Brazilian Institute of

Geography and Statistics) (IBGE, 2008) points out

that in 2008, 65% of the population did not have

access to the Internet.

In addition, important data from the Ministry of

Education in Brazil (MEC, 2007) reveal that about

30 million of Brazilians are functionally illiterate,

defined as the population over 15 years old and less

than 4 years of schooling (21.6% of the population).

Using a broader concept of functional illiteracy,

according to a survey from Paulo Montenegro held

in 2007 (IPM, 2007), the majority (64%) of

Brazilians between 15 and 64 years old and more

than 4 years of schooling reach no more than the

degree of rudimentary literacy, i.e., they have only

ICEIS 2010 - 12th International Conference on Enterprise Information Systems

the ability to locate explicit information in short

texts or make simple math, they are not able to

understand longer texts. This data illustrates only

part of the challenge that we face in terms of

designing systems, which should include all these

users. In this context it has become a major concern

to allow access to online content available from SNS

to all people in a more "natural" and efficient way.

Thus, it is extremely important to recreate

methods to permit the effective access and use of

information conveyed in digital media, for all. This

could be materialized with the ISN concept. We

understand ISN as a “virtual communication space”

based on the concept of social networks, which is

inclusive and allows the community to share

knowledge about the community know-how. This

space has to facilitate “exchange” (of knowledge,

goods and services) in accordance to the

collaborative (project team, partners, community)

system conception.

It is also worth to mention that in an ISN there

are not target users, but all users are relevant and

should be included without discrimination. Thus,

there may be people without skills to handle certain

technological features of the system and

consequently without knowledge to find information

that they need in the system. Moreover, those users

most often use colloquial terms to express

themselves through the system. For example, they

may use the term "postinho" (in Portuguese) instead

of "Basic Health Unit" (formal). They use terms that

make sense to them, but in fact, these expressions

semantically mean the same. So when someone is

trying to retrieve information from the ISN, these

factors must be taken into account by the search

engine. On the other hand, when a user searches for

something in a non-formal or not refined way and,

the same concept but in its formal way (cult) is

returned, this represents an opportunity for learning.

Therefore, we should seek for a computational

search solution that takes into consideration the

meaning that is adopted or emerges in the context of

use of that network; i.e. the meaning that people

bring to the network, and those that are constructed

by using the system over time (through interaction).

This may facilitate and provide better access to the

content generated by users of the network.

3 ANALYSING SEARCH

SCENARIOS OF AN ISN

From a practical point of view, the e-Cidadania pro-

ject resulted in the ‘Vilanarede’

(www.vilanarede.org.br) ISN system. This system

has represented an opportunity to investigate the

interaction behavior of representative users in a

developing country. As a direct activity of the

project, we have conducted the 8th Participatory

Workshop, in a telecenter located at ‘Vila União’,

neighborhood of the Campinas, Brazil. In this

workshop we developed an activity related to search

in the ISN. The objective was to observe some major

points including: (1) How would the users build

understanding of the search engine? (2) Which key-

words would they use? (3) Would they have any

difficulty in completing the proposed scenarios? and

(3) What would be their satisfaction with the search

results?

A task sheet with 4 search scenarios was

presented to each pair of participants, and a form

was prepared to the observers (researchers) of the

activity. We had 7 pairs of users in total. An initial

instruction about the activity was given to the

participants. The pairs were formed by the users

themselves, and for each scenario the pair should

write the words used in the search and the title of the

announcements found. Resulting from this activity,

we had both the sheet tasks filled by the pairs of

users and the observation forms filled out by the

observers. Besides, the activity was filmed and there

was audio recording of each pair during the task

execution. The 4 search scenarios were:

Scenario 1: Find out announcements on how to

popularize the ‘VilanaRede’.

Scenario 2: Find out announcements of mango

(fruit) in ‘VilanaRede’.

Scenario 3: Find out announcements related to food

in‘VilanaRede’.

Scenario 4: Find out announcement related to

religion item combined with handicraft in

‘VilanaRede’.

Each scenario intended to verify whether

semantic capacity was needed for the search

mechanism. The time for the completion of the

scenarios was approximately 45 minutes. After the

execution of the search scenarios, a general

discussion was conducted to get the general

impression of users about the activity. During this

discussion, several interesting stories were collected.

In Scenario 1, we wanted to observe whether

users would use synonymous of “popularize” to find

the announcements. Some pairs had difficulty to

understand the scenario, as well as difficulty in

choosing the terms for the search. However some

pairs associated the word "popularize" to "divulge"

NEW PERSPECTIVES FOR SEARCH IN SOCIAL NETWORKS - A Challenge for Inclusion

and quickly found related announcements. In this

scenario one pair used some unusual keywords such

as: "boca-a-boca” (a popular expression used in

Brazil that means “orally passing information from

person to person”), “email”, “phone” and “posters”.

By using the term "boca-a-boca" in order to find

announcements about how to divulge the site,

unusual results also appeared as an advertisement for

"Bife de casca de banana” (steak of banana peel). It

happened because in one of the comments of this

announcement we find "I'm with water in my mouth

(boca)” in reference to the announcement of "steak

of banana peel”. Phrases for search like "divulgation

of the ‘Vilanarede’" or verbs such as "to popularize

announcement" or "advertising Vila” were also used

in this scenario.

In Scenario 2, we wanted to verify if users would

find any announcement related to mango (fruit) in

the application. There was no announcement about

the mango fruit in the system. However there was an

announcement about mangá (cartoon) and it was

written without the acute accent in the word

(‘manga’ in Portuguese, which is mango fruit in

English). In this scenario, users mainly used the

keywords: "mango (fruit)", "fruit", "mango",

"mango fruit", "mango / fruit". Some pairs were

uncertain if they would have to put the keyword

"fruit" or not. Note that in a semantic search, by

putting the key-word “fruit”, the application should

return all the announcements with mango (fruit), in

the case of announcements semantically related to

fruit.

In Scenario 3, we wanted to see whether users

would use the keyword "food" in the search or they

would make a search for specific foods through the

search engine. As a result, when users tried the

keyword "food", the system returned nothing.

However there are several announcements on food

in the system: the sale of “salgadinhos” (homemade

snacks), “pão de queijo” (cheese bread) and others.

Among the relevant considerations from the

observers, during the execution of this scenario users

said that the system should relate “salgadinhos”

(homemade snacks), “pão de queijo” (cheese bread)

and “Bife de casca de banana” (steak of banana

peel) with the concept of food. And this makes sense

because semantically all of these are food. During

the discussion phase one of the users commented:

"Using food is easier because it already covers

everything," i.e., all types of food in the system.

Another said: "To be more 'lean' and practical for

those who are starting (in terms of computer

literacy), like us, when we enter “food”, it should

return a variety of foods due to our difficulty." Yet

another user says: "Maybe to use food does not help

in the search of something more specific, but if it is

something that we have no knowledge of the

domain, or we do not know what to look for, the tool

would be useful and helpful." The main keywords

used in this scenario were "food", "comida caseira"

(homemade cooking), "food sale", "salgado"

(homemade snacks), "salgadinhos"(small homemade

snacks), "salgadinho frito" (fried homemade

snacks), pies, "doces" (sweets), "pão-de-queijo

(cheese bread), "docinhos” (small sweets), cake,

pastel and “brigadeiro” (chocolate sweet). Note that

users utilize several variations in words such as

“homemade snack”, "small homemade snack" and

"fried homemade snacks".

With Scenario 4, we aimed to determine which

keywords users would use when looking for a

specific announcement. One of the observers

indicated that the pair found the "Saint Anthony"

because they already knew that this announcement

was in the system. The same was reported by several

other observers. The vast majority of the pairs used

the keywords: "homemade craft", "Crafts saint",

"holiness", "holy" and "saints". Users found the

desired information successfully. But one of the

pairs put keywords like: "Orisha", "Orisha of cloth",

"religious" and "sculpture" and didn’t find out any

announcement. Several observers noticed that the

subjects utilize terms from their own colloquial

language in the search; examples can be seen as

"manga rosa" (pink mango), "manga coquinho"

(coconuts mango), "tutu de feijão" (tutu bean),

"boca-a-boca" for the term “divulge”, “small

sweets”, "little homemade snack" and "Orisha". Also

in several occasions the pairs discussed before

reaching an agreement on which word to use in the

search.

Another interesting result was obtained by the

analyze of the interaction of a deaf-mute user with

search mechanisms. We could observe that this user

has some difficult related to word meanings. We

observed that he does not know some words, and use

the same hand signal to several different words; he

has difficult in writing and make different meaning

associations, because what make sense for them

(many deaf-mute people) is not words, but signals.

The user had difficult in understanding the scenario

1, since the words popularize, advertise,

advertisement and disclose have the same hand

signal in his language. Moreover we could see that

the user understands different some words that has

the same meaning; his behavior during the search

was not confident neither independent on

performing the tasks, and the user asked a lot of

ICEIS 2010 - 12th International Conference on Enterprise Information Systems

questions to the observer.

Additionally, general results indicate that users

from this context under study (prospective users of

an ISN) had difficulty with the search button; in

other words, they do not have a clear concept about

the act of "searching" in an application on the

Internet. Some users had no idea about the scope of

searching. They do not know if that search is only

for the announcements in the ‘Vilanarede’ system

which they are using or whatever the term they type

the system will return successful results. This stay

explicit in a description from a user who said:

"Search fondée because it is something chic”.

However another report from other user says:

"Fondée is very chic, we do not have it here in our

network... we will not put it in the search because

the network is ours, it is “poor”... and it will not

have fondée...". This statement shows that the

second user has the notion of the search scope,

which will be just within the announcements from

that social network system, so as there were any

announcements about fondée, nothing would be

returned.

Even with this lack of sense about the search

scope, one of the observers explains that users stay

surprised with the power of the search, and they

explored and tested it easily. This is confirmed due

to the users’ behavior during the execution of the

activity. Positive results were obtained from it. From

the data filled by the observers’ formularies, it is

possible to indicate that approximately 80% of the

pairs proved be safe during the performance of the

task. Approximately 80% of the pairs proved be

independently by performing the scenarios. Around

60% of the pairs did not make a lot of questions to

the facilitator during the task. In the discussion after

the activity, users said that they had to reason more

to perform the search, making exchange of words

and testing various alternatives. More details from

this experiment can be seen in Reis et al. (2010a).

These practical results show that users’

colloquial language should be considered during the

development of more appropriate search engines.

Moreover, people in a social network can create

their vocabulary, sharing meanings in the

community. The results showed us that it is

necessary to construct computationally tractable

models from the semantic point of view that come

out from the network itself. Semantics here is

understood as the interpretation of signs (Peirce

1931-1958, cf 2.228) by individuals and their

association with real world elements. This

interpretation is socially contextualized; i.e.

individuals and communities may have different

interpretations for the same sign and a sign may

connote different meanings depending on the

context applied.

As a theoretical reference for our proposed

approach, we have used the Semantic Analysis

Method (SAM) from the Organisational Semiotics

(Liu, 2000). This method assists the users or

problem owners in eliciting and representing

meanings in a formal and precise model. An

Ontology Chart (OC) describes a view of

responsible agents in the focal domain and their

behavior or action patterns named affordances (Liu,

2000). Some basic concepts of SAM adopted in this

paper are based in Liu (2000). In the next section we

outline a new approach to build Web ontologies

based on this method as well as a novel search

mechanism that utilizes it.

4 TOWARD A NEW SEARCH

MECHANISM

General difficulties faced by users to get information

in the Web can be mainly explained by: (1) overload

of information presented in the system; and (2)

problems related to the contextualization of meaning

for the terms used. As an attempt to solve this

problem, we have investigated approaches that can

result in better and more appropriate search engines

for ISN.

In a social network the “emergence” of meaning

is an ongoing process in which meanings and

interpretations are constructed, used and shared

through the system based on the interactions and

expressions of users. These interpretations expressed

by users in the system could be computationally

represented. Several improvements could be

achieved such as semantic models that can make the

social network context more faithful resulting in

more adequate search engines.

To accomplish that, we propose a search engine

informed by a Semiotic approach. We have

developed a semi-automatic process to model the

semantics in the ISN using SAM, and we use the

outcome of this process in the search engine.

4.1 Modelling the Ontologies for ISN

In the ‘VilanaRede’ system, users express

themselves through their profiles, announcements of

products, services and ideas created by them; and

they communicate mainly through commentaries

about the announcements and chats between

NEW PERSPECTIVES FOR SEARCH IN SOCIAL NETWORKS - A Challenge for Inclusion

members of the network. These data are stored in the

ISN system database and from these dada we

represent the semantics used in the social network in

a structure called ‘Semiotic Web ontology’.

This structure is a semantic model

(computationally tractable ontology) constructed

from a semi-automatic process based on the SAM

along with the vocabularies shared in the social

network. The theoretical and methodological

concepts described in the SAM are used in

conjunction with other technologies from the

Semantic Web field to describe computationally

tractable ontologies using the Web Ontology

Language (OWL) (W3C, 2004). The idea is to

incorporate the concepts of particular Agents (roles)

and Affordances (pattern of behavior) arising from

the SAM into an expanded and more representative

Semantic Web ontology. It is worth to mention that

it is not the goal to create a “perfect ontology” from

a theoretical point of view, but to produce practical

and immediate results for search in ISN. Therefore

some properties from the OC may not be fully

transcribed to OWL, while other aspects such as

agent-affordance relationship are emphasized.

This approach is justified from a Semiotic

perspective, since the signs are socially constructed.

Thus, a computational model that represents the

semantics of an SNS should contain the agents that

interpret the socially shared concepts. With this

approach we incorporate and take into account to

Semantic Web ontologies concerns and possible

representations arising from the Ontology in a

Semiotic perspective. In addition to agents and

affordances, we have observed that Semantic Web

ontologies also do not incorporate (at least

explicitly) the idea of ontological dependency

relations, the existential relation in the model. The

approach is also justified by the representational

limitations shown in literature (e.g. Tanasescu &

Streibel (2007)) regarding the use of ontologies in

computing and their expressivity.

As a conceptual model, in this computational

approach based on SAM, the agents have

behavior(s) (affordances) related to a concept. For

example, a seamstress, which is an agent, can sew a

“manga” (it means sleeve in English). Sewing is a

pattern of behavior of a seamstress (in other words

an affordance). “Manga” is a concept that can have

several different meanings in Portuguese (It can

mean sleeve, fruit, color, etc.), but in this context

due to the affordance and the agent, the meaning of

“manga” is more closely linked to shirt and not, for

example, to “manga” fruit (mango in English) that

can also be represented in the model, as illustrated

by Figure 1.

Figure 1: Modelling meanings: an example of polysemy

using agents and affordances.

Figure 1 illustrates an example of modeling in

which the grocer and the seamstress are agents that

have affordances connected to specific concepts.

And this model can also have specific ‘is-a’

relationships; for example ‘manga rosa’ is a specific

kind of mango. This also shows that concepts can be

related to several agents and affordances and with

other concepts, constituting relations and

representations that make more complete ontologies

compared to conventional ontologies described

purely for a domain. For example, ‘manga’ can also

mean a color for a painter who is searching

something in the network, as well as ‘manga’ can

have any synonym that makes sense for an agent ‘Y’

modeled from the data of the social network. We can

see other examples like: ‘crane’ mean a bird or a

type of construction equipment and we can model it

using the agents and their affordances in a ‘Semiotic

Web Ontology’.

To develop this representation, we propose an

assisted method (semi-automatic) with several

distinct steps, which is a novel approach to create

ontologies; the method is illustrated in Figure 2. It

includes: (1) the extraction of terms from the

database of the ISN system; (2) the creation of an

OC (from SAM); and (3) the creation of the final

OWL ontology.

In this assisted process, the first step is to process

the data from the system database. This step takes

into account the social relations in the network, and

provides the necessary well defined data (a list of

concepts, agents and affordances, etc) to build the

semantic model. Related to this phase, we apply

algorithms for text extraction and analysis and data

from the database of the ISN system. For this we

propose the use of keyphases extractors like KEA

(Medelyan, 2006) and tools for term extraction and

creation of concepts such OntoLP (Ribeiro & Vieira,

2008).

ICEIS 2010 - 12th International Conference on Enterprise Information Systems

Figure 2: Illustration of the Semi-Automatic Tool.

The next step is the building of an OC (from

SAM) by an ontology engineer. This intermediate

ontology diagram is important to identify the

possible agents in the ISN and their patterns of

behavior.

In the third step, from the OC, a set of specific

heuristics and rule transformations is applied to

derive an initial OWL ontology (computationally

tractable), extending the computational development

of the SONAR CASE tool (see Santos et al., 2008).

Bonacin et al. (2004) proposed a heuristic to

transform OC into system design diagrams; however

those heuristic must be adapted to our purpose. In

this step the ontology engineer can also be assisted

by existing tools for Ontology Learning and other

data extracted from the system. As suggested by

Maedche & Staab (2001), Ontology Learning can be

helpful for ontology engineers to build these

artifacts. In the next sub-section we draw up an

Inclusive Search mechanism.

4.2 Outlining an Inclusive Search

Engine

After the creation of the semantic model, it is used

by the ISN search engine. When the user is logged in

the social network system and he/she enters with

some search term(s) in the search engine, the system

starts a process of making relationships of this/these

keyword(s) with the available ‘Semiotic Web

Ontology’. The purpose is to perform a search in the

database system and to return semantically related

results. For example, suppose the user types the term

"small snack". If there is nothing in the system with

this expression, from the analogies and semantic

relations made, the system may return some other

types of food semantically close. Likewise if the

user enters the word ‘food’, all advertisements

related to food should be returned.

There are several architectural proposals for

semantic search solutions, as described in Mangold

(2007) and also in Fang et al. (2005). The decisions

and architectural strategies for resolving the

semantic search in this implementation is carried out

in accordance with the requirements of an ISN. The

main difference in the search solution of this

proposal is to take into account information

regarding the user that is making the search (from

his/her profile) and the user that produces the

content. See Figure 3 that illustrates this idea.

Figure 3: Illustration of the Search Mechanism.

In this strategy, the user profile is important due

to the possibility of discovering a context for the

search terms. From the user profile, we aim to

identify the agent represented in the ontology. Thus

we can prioritize (or even limit) the search space,

making a relation between the user and the semantic

model generated. For instance, imagine that a

biologist is logged into the system (we could find

that a user is a biologist based on his/her profile) and

requests a search with the keyword ‘crane’. If there

exist a relation between the ‘biologist’ agent and the

term ‘crane’ in the ontology, most likely the results

(announcements) that could be returned first (ranked

NEW PERSPECTIVES FOR SEARCH IN SOCIAL NETWORKS - A Challenge for Inclusion

first) should be related to the concept of crane as a

‘bird’, not the other meaning(s) of this word.

However, to a civil engineer that searches the same

word, maybe the results that most interest him / her

refers to the construction equipment and not the bird.

We do not mean that other results are not required or

may not be returned in response to the search, (the

engineer may want to know about this kind of bird),

but the announcements from the social network that

relates ‘crane’ with a construction equipment must

have greater relevance in the ranking of results.

The agent-affordance relation is also used to

indicate the probable meaning of the words in the

announcement. For example, we could verify

whether the word ‘crane’ is about ‘bird’ or

‘construction equipment’ in a particular

announcement that mentions the word ‘crane’ based

on the user that entered such information, or based

on the commentaries made on this announcement.

Then, if the user who submitted the announcement is

a ‘biologist’ agent, ‘crane’ would be most likely a

‘bird’ in this announcement. In a similar way, if the

advertiser is a civil engineer, also ‘crane’ would

mean most likely a ‘construction equipment’. We

also could have relationships between agents and

could verify how much an agent is semantically

close to another and indicate the probable meaning

based on this aspect.

5 DISCUSSION

The support for better results from the search engine

in this approach demands a careful modeling

procedure. Different signs with the same meaning

(synonyms) coming from different virtual

communities of the social network can be discovered

having the opportunity to be represented in the

ontology; such signs and meanings can be purely

regional. They could not be present in formal

dictionaries or thesauri generally used by

conventional search mechanisms. Furthermore

because they are cultural expressions emerging from

the social network, the ontology would potentially

provide smarter and richer search results when

compared to ontologies based on domains or formal

definitions.

The approach provides means to discover and

distinguish the meanings used in the SNS,

representing them through the agents in the

‘Semiotic Web ontology’. Differently from

conventional computing ontologies, and other

approaches to semantic representation, our proposal

involves adding the agents and affordances concept.

This addition can cooperate for richer search results

treating the polysemy problem in not restricted or

controlled language contexts. Moreover, the

inclusion of the agents and other concepts from

SAM in the Web ontology can help improving the

search mechanism, generating results more adequate

to a SNS context.

In the case of users with limited literacy and with

difficulty in dealing with technological artifacts

(digitally illiterate), it is important to give to them

the opportunity to perform the search using their

daily language since usually is what make sense to

them, and to provide search results more natural and

adequate to their live. Thus, the search engine

should reflect the semantic reality of the social

network users, and therefore the required

information will be easier to find. A search engine

with such characteristics could create opportunities

for inclusion, since the method for building the

semantic model as well as the strategies in the search

engine to use the ontology suggests that the search

results returned will tend to make more sense for the

user that searches.

Some recent studies in the literature address

search solutions for SNS (e.g. Vieira et al. (2007),

Perisic & Haynes (2009) and Gürsel & Sen (2009)).

These works are particularly focused on searching

just users’ profile in the network and to develop

solutions in this direction; the work of Choudhari et

al. (2008) makes progress in the development of

semantic search in social networks, however their

work have the same limitation and does not use

ontologies to perform the search.

Regarding semantic search but not strictly related

to SNS context, there exist various proposals and

solutions as illustrated by the survey of Mangold

(2007) and Wei et al. (2007). Ontology based

semantic search solutions (e.g. Bonino et al. (2004)

and Fang et al. (2005)) as well as ontology based

query expansion (e.g. Hoang & Tjoa (2006) and

Bhogal et al. (2007)) have enhanced techniques for

semantic search applications. In order to

implementing a solution and make improvements to

a search engine of an ISN, future research of our

work includes a detailed observation of more

ontology based query expansion approaches in the

literature to using the ‘Semiotic Web ontology’

method. Other approaches (e.g. Tvarozek et al.

(2008)) have trying to take advantage of the ‘faceted

browsing paradigm’ and employ an integration

solution between semantic search and visual

navigation in graphs using the idea of social

networks.

Previous work conducted by Reis et al. (2010b)

ICEIS 2010 - 12th International Conference on Enterprise Information Systems

have develop a study on the challenges related to

search in ISN; the authors propose recommendations

for a search engine better suited to this kind of

system. To the best of our knowledge were not

found in the literature so far investigations that have

specifically focused on semantic search in SNS

considering aspects of accessibility and inclusion.

We agree that the development of a search engine on

an ISN should include these new challenges.

We also argue that the approach developed in

this paper can improve and expand methodologically

and technologically Semantic Web techniques, such

as Web ontologies, illustrating immediate and

practical results for better SNS search engines. This

approach differs from others, since the search

solution outlined tries to derive the term meanings of

the search and also the term meanings of the content

produced by users in the system, as information

from the users profile together with their behaviour

and roles. The solutions presented in literature so far

do not deal directly with this approach. Future

experiments with real users can show whether our

approach can bring promising benefits revealing

search results more suitable to the context of social

and digital inclusion, and also to SNS in general.

6 CONCLUSIONS

Social network systems may provide inclusive

access to digital information for people, creating

situations where the users’ diversity is respected and

the access difficulties minimized. This is the purpose

of the Inclusive Social Networks (ISN). It is

important to provide information retrieving in a

more natural way from the user’s viewpoint, with

results that make sense to people. Therefore more

suitable mechanisms for search should take into

account the meanings created, shared and used by

people in the social network.

This paper presented new perspectives for search

in ISN which consider the inclusive social context. It

showed the outcomes of an analysis about how to

improve a search mechanism considering aspects

related to the digital and social inclusion. We could

verify with real users, that semantic aspects can

make a difference for the users to reach information,

and that the current syntactic search engines are not

enough to an ISN context. Inspired on the practical

context of ISN users, this paper outlined a novel

method based on Semantic Analysis Method from

Organisational Semiotics to build more

representative Web ontologies, as well as

requirements of a software tool that materializes

these ideas as a process. Besides, it showed

strategies for using the proposed ontology with the

search engine to provide more precise search results.

As further work, the goal of this research is to

improve (in the implementation sense) the ideas

drawn up for the search mechanism described in this

paper. For that, we aim to develop the semi-

automatic tool for building ‘Semiotic Web

ontology’, as an extension of the SONAR tool,

including the heuristics and rule transformations to

build the OWL ontology aided from OC.

Furthermore we intend to develop a pilot

implementation of this search engine based on the

‘Semiotic Web ontology’ in the ‘VilanaRede’

system, using and improving the strategies

mentioned in this paper; also the work involves new

practical experiments with real users, utilizing this

novel search mechanism in order to evaluate and

validate the solution with empirical results.

ACKNOWLEDGEMENTS

This work is funded by Microsoft Research -

FAPESP Institute for IT Research (proc. n.

2007/54564-1) and by CNPq/CTI (680.041/2006-0).

The authors also thank colleagues from CTI, IC –

Unicamp, NIED, InterHAD and Casa Brasil for

insightful discussion.

REFERENCES

Baranauskas, M. C. C., 2007. e-Cidadania: Systems and

Methods for the Constitution of a Culture mediated by

Information and Communication Technology.

Proposal for the Microsoft Research-FAPESP

Institute.

Bhogal, J., Macfarlane, A., Smith, P., 2007. A review of

ontology based query expansion. Information

Processing & Management, Vol. 43, No. 4, pp. 866-

886.

Bonacin, R., Baranauskas, M. C. C., Liu, K., 2004. From

Ontology Charts to Class Diagrams: semantic

analysis aiding systems design. In: Proc. of the 6th

International Conference on Enterprise Information

Systems. Porto, Portugal.

Bonino, D., Corno, F., Farinetti, L., Bosca, A. 2004.

Ontology Driven Semantic Search. WSEAS

Transaction on Information Science and Application,

Issue 6, Vol. 1, pp. 1597-1605.

Boyd, D. M. & Ellison, N. B., 2008. Social Network Sites:

Definition, History, and Scholarship. Journal of

Computer-Mediated Communication. Number 13. pp.

210-230.

NEW PERSPECTIVES FOR SEARCH IN SOCIAL NETWORKS - A Challenge for Inclusion

Choudhari, A., Jain, M., Sinharoy, A., Zhang, M., 2008.

Semantic Search in Social Networks. <http://

www.cc.gatech.edu/projects/disl/courses/8803/2008/pr

oject/project_deliverables/group22/proposal.pdf>.

Accessed on January, 2010.

Fang, W., Zhang, L., Wang, Y., Dong, S., 2005. Toward a

Semantic Search Engine based on Ontologies. In Proc.

of the 4th International Conference on Machine

Learning and Cybernetics. Guangzhou, China.

Volume: 3, pp. 1913-1918.

Gürsel, A & Sen, S., 2009. Improving search in social

networks by agent based mining. In Proc. of the 21st

International joint conference on Artificial intelligence

table of contents. Pasadena, California, USA. pp.

2034-2039.

Haynes, J. & Perisic, I., 2009. Mapping Search Relevance

to Social Networks. In Proc. of 3rd Workshop on

Social Network Mining and Analysis. International

Conference on Knowledge Discovery and Data

Mining. Paris, France.

Hoang, H. H. & Tjoa, M., 2006. The State of the Art of

Ontology-based Query Systems: A Comparison of

Existing Approaches. In Proc. of IEEE International

Conference on Computing and Informatics (ICOCI).

Kuala Lumpur, Malaysia.

IBGE, 2008. Acesso à Internet e posse de telefone móvel

celular para uso pessoal 2008. Retrieved January,

2010 from <http://www.ibge.gov.br/home/estatistica/

populacao/acessoainternet2008>

IPM, 2007. Indicador Nacional de Analfabetismo

Funcional. Retrieved January, 2010 from

<http://www.smec.salvador.ba.gov.br/site/documentos/esp

aco-virtual/espaco-dados-

estatisticos/indicador%20de%20analfabetismo%20fun

cional%202007.pdf>.

Liu, K., 2000. Semiotics in information systems

engineering, Cambridge University Press.

Maedche, A. & Staab, S., 2001. An Ontology Learning for

the Semantic Web. IEEE Intelligent Systems. Volume

16, Issue 2. pp. 72 – 79.

Mangold, C., 2007. A survey and classification of

semantic search approaches, Int. J. Metadata,

Semantics and Ontology, Vol. 2, No. 1, pp.23–34

MEC, 2007. Retrieved November, 2009 from

<http://portal.mec.gov.br>.

Medelyan, O., 2006. Semantically Enhanced Automatic

Keyphrase Indexing. In Proc. of Women in Machine

Learning (WiML) Workshop co-located with the

Grace Hopper Celebration of Women in Computing.

San Diego, USA.

Neris, V. P. A., Almeida, L. D., Miranda, L. C., Hayashi,

E., Baranauskas, M. C. C., 2009. Towards a Socially-

constructed Meaning for Inclusive Social Network

Systems. In Proc. of International Conference on

Informatics and Semiotics in Organisations - ICISO.

Beijing, China. pp. 247-254.

Nielsen, 2009. Global Faces and Networked Places. The

Nielsen Company USA. Retrieved July, 2009 from

http://blog.nielsen.com/nielsenwire/wp-content/uplo

ads/2009/03/nielsen_globalfaces_mar09.pdf.

Peirce, C. S., 1931-1958. Collected Papers. Cambridge,

Mass: Harvard University Press.

Reis, J. C., Bonacin, R., Baranauskas, M. C. C., 2010a.

Analysing Search in Inclusive Social Network

Services. IC-10-02, www.ic.unicamp.br/~reltech.

Reis, J. C., Baranauskas, M. C. C., Bonacin, R., 2010b.

Busca em Sistemas Sócio-Culturais Online: Desafios e

Recomendações (Paper submitted to XXXVII

Seminário Integrado de Software e Hardware -

SEMISH 2010) (In Portuguese).

Ribeiro, L. C. & Vieira, R., 2008. OntoLP: Engenharia de

Ontologias em Língua Portuguesa. In Seminário

Integrado de Software e Hardware - SEMISH. Anais

do XXVIII Congresso da Sociedade Brasileira de

Computação. Porto Alegre: SBC, v. 1. p. 1-15. (In

Portuguese).

Santos, T. M., Bonacin, R., Baranauskas, M. C. C.,

Rodrigues, M. A., 2008. A Model Driven Architecture

Tool Based on Semantic Analysis Method. In Proc. of

10th International Conference on Enterprise

Information Systems. Barcelona, Spain. V. 2 pp. 305-

310.

Stamper, R. K., 2001. Organisational Semiotics:

Informatics without the Computer? In Information,

Organisation and Technology: Studies in

Organisational Semiotics, eds. K. Liu, R. Clarke, P. B.

Andersen and R. K. Stamper. Kluwer Academic

Publishers.

Tanasescu, V. & Streibel, O., 2007. Extreme Tagging:

Emergent Semantics through the Tagging of Tags. In

International Workshop on Emergent Semantics and

Ontology Evolution (ESOE2007). Busan, Korea.

Tvarožek, M., Barla, M., Frivolt, G., Tomša, M., Mária,

B., 2008. Improving Semantic Search via Integrated

Personalized Faceted and Visual Graph Navigation.

In SOFSEM 2008: Theory and Practice of Computer

Science. Lecture Notes in Computer Science -

Springer Berlin / Heidelberg. Vol. 4910, pp. 778-789.

Vieira, M. V., Fonseca, B. M., Damazio, R., Golgher, P.

B., Reis, D. C., Neto, B. R., 2007. Efficient Search

Ranking in Social Networks. In Proc. of 16th ACM

Conference on information and knowledge

management. Lisbon, Portugal. pp. 563-572.

Wei, W., Barnaghi, P. M., Bargiela, A., 2007. The

Anatomy and Design of a Semantic Search Engine.

Tech. rep., School of Computer Science, University of

Nottingham Malaysia Campus.

W3C, 2004. “OWL-Web Ontology Language”,

Recommendation 10 February 2004. Retrieved March,

2009 from http://www.w3.org/TR/owl-features.

ICEIS 2010 - 12th International Conference on Enterprise Information Systems